feat: install skills via git sparse-checkout in platform install scripts (#390)

Adds a skills installation phase to all three install scripts (sh, ps1, cmd).
Uses git sparse-checkout to fetch only apps/skills/ from the repo at the
release tag, then copies into ~/.claude/skills/ and ~/.config/agents/skills/.
Gracefully skips if git is unavailable or the clone fails.

For provenance purposes, this commit was AI assisted.
This commit is contained in:
Michael Ramos
2026-03-25 00:17:19 -07:00
committed by GitHub
parent 919f582e0c
commit f2a05ece4f
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---
name: plannotator-compound
description: >
Analyze a user's Plannotator plan archive to extract denial patterns, feedback
taxonomy, evolution over time, and actionable prompt improvements — then produce
a polished HTML dashboard report. Use this skill when the user says things like
"/compound-planning", "analyze my plans", "plan analysis", "what are my denial
patterns", "why do my plans get denied", "compound planning report", "plan
insights", or "analyze my planning data". This is a user-invoked skill only —
do not trigger automatically. The user must explicitly request it.
---
# Compound Planning Analysis
You are conducting a comprehensive research analysis of a user's Plannotator plan
archive. The goal: extract patterns from their denied plans and annotations, reduce
them into actionable insights, and produce an elegant HTML dashboard report.
This is a multi-phase process. Each phase must complete fully before the next begins.
Research integrity is paramount — every file must be read, no skipping.
## Phase 0: Locate the Plans Directory
Check for `~/.plannotator/plans/`. If it exists and contains `.md` files, proceed.
If not found, ask the user:
> "I couldn't find plans at ~/.plannotator/plans/. Where is your plans directory?"
Once you have the path, verify it contains files matching `*-denied.md` and/or
`*.annotations.md`. If neither exist, inform the user there's no denial/annotation
data to analyze and stop.
## Phase 1: Inventory
Count and report the dataset:
```
- *-approved.md files (count)
- *-denied.md files (count)
- *.annotations.md files (count)
- *.diff.md files (count)
- Date range (earliest to latest date found in filenames)
- Total days spanned
- Revision rate: denied / (approved + denied) — this is the "X% of plans
revised before coding" stat used in dashboard section 1
```
Also run `wc -l` across all `*-approved.md` files to get average lines per
approved plan. This tells the user whether their plans are staying lightweight
or bloating over time. You do not need to read approved plan contents — just
their line counts. If possible, break this down by time period (e.g., monthly)
to show whether plan size changed.
Dates appear in filenames in YYYY-MM-DD format, sometimes as a prefix
(2026-01-07-name-approved.md) and sometimes embedded (name-2026-03-15-approved.md).
Extract dates from all filenames.
Tell the user what you found and that you're beginning the extraction.
## Phase 2: Map — Parallel Extraction
This is the most time-intensive phase. You must read EVERY denied plan and EVERY
annotation file. Do not skip files. Do not summarize early.
**Important:** Do NOT read approved plan files. They are counted in the inventory
for context (total volume, approval rate) but are not analyzed for feedback
patterns. Only `*-denied.md` and `*.annotations.md` files contain the feedback
data this analysis needs.
### Batching Strategy
The approach depends on dataset size:
**Small datasets (< 40 total files):** Read all files directly — no need for
parallel agents. Just read them sequentially and proceed to Phase 3.
**Medium datasets (40-120 files):** Split into 2-4 parallel agents by file type
and/or time period.
**Large datasets (120+ files):** Split into batches of ~40-60 files per agent.
Split by the natural time boundaries in the data (months, quarters, or whatever
groupings produce balanced batches). If one time period dominates (e.g., the most
recent month has 3x the files), split that period into two batches.
Launch all extraction agents in parallel using the Agent tool with
`run_in_background: true`.
### Output Files
Each extraction agent must write its results to a clean output file rather than
relying on the agent task output (which contains interleaved JSONL framework
logs that are difficult to parse). Instruct each agent to write to:
```
/tmp/compound-planning/extraction-{batch-name}.md
```
Create the `/tmp/compound-planning/` directory before launching agents. The
reduce agent in Phase 3 will read these clean files directly.
### Extraction Prompt for Denied Plans
Each agent for denied plans receives this instruction (adapt the time period,
file glob, and output path):
```
You are extracting structured data from denied plan files for a pattern analysis.
Directory: [PLANS DIRECTORY]
Files to read: All *-denied.md files with dates in [TIME PERIOD]
Output: Write your complete results to [OUTPUT FILE PATH]
Read EVERY matching file. For EACH file, extract:
- The plan name/topic
- The denial reason or feedback given (look for reviewer comments, annotations,
revision requests — capture the actual words used)
- What was specifically asked to change
- The type of feedback (let the content determine the category — don't force-fit
into predefined types. Common types include things like: scope concerns,
approach disagreements, missing information, process requirements, quality
concerns, UX/design issues, naming disputes, clarification requests,
testing/procedural denials — but the user's actual patterns may differ)
- Any specific phrases or recurring language from the reviewer
- The date
Do NOT skip any files. One entry per file.
Format each entry as:
**[filename]**
- Date: ...
- Topic: ...
- Denial reason: ...
- Feedback type: ...
- Specific asks: ...
- Notable phrases: ...
---
After processing all files, write the complete results to [OUTPUT FILE PATH].
State the total file count at the end of the file.
```
### Extraction Prompt for Annotation Files
Annotation files have a different structure — they contain inline comments,
highlights, and feedback left on specific sections of plans. Each agent for
annotations receives this instruction:
```
You are extracting structured data from annotation files for a pattern analysis.
Directory: [PLANS DIRECTORY]
Files to read: All *.annotations.md files with dates in [TIME PERIOD]
Output: Write your complete results to [OUTPUT FILE PATH]
Read EVERY matching file. For EACH file, extract:
- The plan name/topic it annotates
- Every individual annotation/comment made (there may be multiple per file)
- For each annotation: the quoted text, what type of feedback it is (correction,
scope concern, design preference, structural request, question, praise,
process directive, etc.), and what section of the plan was annotated
- The overall tone of the feedback
Do NOT skip any files. One entry per file.
Format each entry as:
**[filename]**
- Plan topic: ...
- Annotations found: [count]
- Annotation 1: "[quote or paraphrase]" — Type: ... — Section: ...
- Annotation 2: "[quote or paraphrase]" — Type: ... — Section: ...
- (continue for all annotations in the file)
- Overall tone: ...
---
After processing all files, write the complete results to [OUTPUT FILE PATH].
State the total file count at the end of the file.
```
### While Agents Run
Track completion. As each agent finishes, note the count of files it processed.
Verify the total matches the inventory from Phase 1. If any agent's count is
short, flag it and consider re-launching for the missing files.
If an agent times out (possible with large batches — a batch of 128 files can
take 8+ minutes), re-launch it for just the unprocessed files. Check the output
file to see how far it got before timing out.
## Phase 3: Reduce — Pattern Analysis
Once ALL extraction agents have completed (or all files have been read for small
datasets), launch a single reduction agent.
The reduction agent reads the clean extraction files from `/tmp/compound-planning/`
(not the agent task output files, which contain noisy JSONL framework logs). It
processes all extraction files together and produces the comprehensive analysis.
Give the reduction agent this prompt (adapt the file paths):
```
You are a data scientist conducting the reduction phase of a map-reduce analysis
across a user's plan denial and annotation archive.
Read ALL extraction files at /tmp/compound-planning/extraction-*.md
These files contain structured extractions from every denied plan and annotation
file. Your job: aggregate everything, find patterns, cluster into a taxonomy,
and produce a comprehensive analysis.
Be exhaustive. Use real counts. Quote real phrases from the data. This is
research — no hand-waving, no fabrication.
Produce the following sections:
[... sections listed below ...]
```
The reduction agent's job is to let the data speak. Do not impose a predetermined
framework — discover what's actually there. The analysis must produce:
### 1. Denial Reason Taxonomy
Categorize every denial into a finite set of types that emerge from the data. Count
occurrences. Show percentages. Include real example quotes for each type. Aim for
8-15 categories — enough to be specific, few enough to be scannable. Let the user's
actual feedback determine what the categories are.
### 2. Top Feedback Patterns (ranked by frequency)
The 5-10 most recurring patterns. For each: what the reviewer consistently asks for,
3+ example quotes from different files, and whether the pattern changed over time.
### 3. Recurring Phrases
Exact phrases the reviewer uses repeatedly, with counts and what they signal. These
are the reviewer's vocabulary — their shorthand for what they care about.
### 4. What the Reviewer Values (implicit preferences)
Derived from patterns — what does this specific person care about most? Quality?
Speed? Narrative? Architecture? Process? Simplicity? Rank by evidence strength.
This section should feel like a personality profile of the reviewer's standards.
### 5. What Agents Consistently Get Wrong
The flip side — what recurring mistakes trigger denials? What should agents stop
doing for this reviewer?
### 6. Structural Requests
What plan structure does the reviewer consistently demand? Required sections,
ordering, format preferences, level of detail expected.
### 7. Evolution Over Time
How feedback patterns changed across the time span. Group by whatever natural time
boundaries exist in the data (weeks for short spans, months for longer ones). Did
expectations mature? Did new patterns emerge? What shifted? If the dataset spans
less than a month, note that evolution analysis is limited but still look for any
progression from early to late files.
### 8. Actionable Prompt Instructions
The most important output. Based on all patterns: specific numbered instructions
that could be embedded in a planning prompt to prevent the most common denial
reasons. Write these as actual directives an agent could follow. Be specific to
this user's patterns — generic advice like "write good plans" is worthless. Each
instruction should trace back to a real, frequent denial pattern.
After writing the instructions, calculate what percentage of denials they would
address (count how many denials fall into categories covered by the instructions
vs total denials). Report this percentage — it will be different for every user.
## Phase 4: Generate the HTML Dashboard
Build a single, self-contained HTML file as the final deliverable. Save it to
the user's plans directory as `compound-planning-report.html`.
Read the template at `assets/report-template.html` for the **design language
only**. The template contains example data from a previous analysis — ignore all
data values, quotes, and percentages in the template. Use only its visual design:
colors, typography, spacing, component styles, and layout patterns.
### Design Language (from template)
- **Palette:** Light mode, warm off-white (#FDFCFB), text in slate scale, amber
for highlights/accents, emerald for positive, rose for negative, indigo for
action elements
- **Typography:** Playfair Display (serif, for narrative headings), Inter (sans,
for body/data), JetBrains Mono (mono, for code/phrases) — Google Fonts CDN
- **Layout:** Single-column, max-width 1024px, generous vertical whitespace (128px
between major sections), editorial/narrative-first aesthetic
- **Tone:** Calm, reflective, authoritative. Like a personal retrospective journal,
not a monitoring dashboard.
### Page Frame (header + footer)
Before the 7 sections, the page has:
- **Header:** Report title on the left (Playfair Display, ~36px), project name +
date range below it in light meta text. On the right: file counts in mono
(e.g., "202 denials · 168 annotations · 71 days"). Separated from content by
a bottom border. Generous bottom padding before section 1.
- **Footer:** After section 7. Top border, centered italic Playfair Display tagline
summarizing the corpus (e.g., "Analysis of X denied plans and Y annotation files
from the Plannotator archive.").
### Dashboard Section Order (7 sections)
The report follows this exact section order. Each section builds on the previous
one — the flow moves from "what happened" through "why" to "what to do about it":
1. **The story in the data** — An editorial narrative paragraph (Playfair Display
serif, ~26px) that tells the headline finding in prose. Not bullet points — a
real paragraph that reads like the opening of an article. Alongside it, a KPI
sidebar with 3 key metrics (the top denial percentage, the overall revision
rate, and the number of distinct denial categories found). Use an amber inline
highlight on the most striking number in the narrative.
2. **Why plans get denied** — The taxonomy as a ranked list. Each row: rank number
(mono), category label, a thin 4px progress bar (top item in amber-500, rest
in slate-300), percentage (mono), and for the top entries, a real italic quote
from the data below the label. Show the top 10 categories or however many the
data supports (minimum 5).
3. **How expectations evolved** — One card per natural time period. Each card has:
the period name in serif, a theme phrase in colored uppercase (different color
per period to show progression), a description paragraph, and a stat line at
the bottom (e.g., "X denials · Y narrative requests"). If the data spans less
than 3 distinct periods, use 2 cards or even a single card with internal
progression noted.
4. **What works vs what doesn't** — Two side-by-side cards. Left: green-tinted
(emerald-50/50 bg, emerald-100 border) with traits of plans that succeed for
this reviewer. Right: red-tinted (rose-50/50 bg, rose-100 border) with what
agents keep getting wrong. Both derived from the reduction analysis. Bulleted
with small colored dots. 5-8 items per card.
5. **The actionable output** — The diagnostic payoff. Opens with a Playfair
Display narrative sentence stating how many prompt instructions were derived
and what estimated percentage of denials they address (use the real calculated
percentage from Phase 3, not a generic number). Then the top 3 most impactful
improvements as numbered items, each with an amber number, bold title, and
one-line description. This section bridges the analysis and the full prompt
that follows.
6. **Your most-used phrases** — Grid of chips (2-col mobile, 3-col desktop). Each
chip: monospace quoted phrase on the left, frequency count on the right. White
bg, slate-200 border, rounded-12px. Show 9-12 of the most recurring phrases
found. These should be the reviewer's actual words — their verbal fingerprint.
7. **The corrective prompt** — Dark panel (slate-900 bg, white text, rounded-3xl,
shadow-xl). Opens with a Playfair intro sentence about the instructions. Then
a dark code block (slate-800/80 bg, amber-200 monospace text) containing the
full numbered prompt instructions from Phase 3. Include a copy-to-clipboard
button that works (JS included). Below the code block: a gradient glow card
(indigo-to-purple blurred halo behind a white card) with a closing message
that these instructions are personal — derived from the user's own feedback,
their own language, their own standards.
### Adaptation Rules
- If the user has < 3 months of data, reduce the evolution section to fewer cards
- If the user has no annotation files (only denials), note this in the narrative
and skip annotation-specific insights
- If fewer than 5 denial categories emerge, combine the taxonomy and patterns
sections into one
- If the dataset is very small (< 20 files), the narrative should acknowledge the
limited sample size and frame findings as preliminary
- The number of prompt instructions will vary per user — could be 8 or 20. Don't
force exactly 17. Let the data determine the count.
- The top 3 actionable items in section 5 must be the 3 that cover the largest
share of denials, not the 3 that sound most impressive
### Key Rules
1. Every number must come from the real analysis — no fabricated data
2. Every quote must be a real quote from a real file
3. The taxonomy percentages must be calculated from real counts
4. The prompt instructions must trace back to actual denial patterns
5. The copy button on the prompt block must work (include the JS)
After generating, open the file in the user's browser.
## Phase 5: Summary
Tell the user:
- How many total files were analyzed (denials + annotations)
- The top 3 denial patterns found
- The estimated percentage of denials the prompt instructions would address
- The single most impactful prompt improvement
- Where the report was saved
## Important Notes
- **Research integrity:** Every file must be read. The value of this analysis comes
from completeness. Sampling or skipping undermines the findings.
- **Real data only:** Never fabricate quotes, percentages, or patterns. If the data
doesn't show a clear pattern, say so honestly rather than inventing one.
- **Let the data lead:** The taxonomy, patterns, and instructions should emerge from
what's actually in the files. Different users will have completely different
denial patterns. A user building mobile apps will have different feedback than
one building APIs. Don't assume what the patterns will be.
- **Agent parallelization:** For large datasets, maximize parallel agents to reduce
wall-clock time. The bottleneck is the largest batch — split it.
- **Structured extraction format:** Ask extraction agents to return structured text
with consistent delimiters so the reduce agent can parse reliably.
- **The report is the artifact:** The HTML dashboard is what the user keeps. It
should be beautiful, honest, and useful. Every section should feel like it was
written about them specifically, because it was.
@@ -0,0 +1,795 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Compound Planning — What 370 Files Reveal</title>
<link rel="preconnect" href="https://fonts.googleapis.com">
<link href="https://fonts.googleapis.com/css2?family=Playfair+Display:ital,wght@0,400;0,500;1,400&family=Inter:wght@300;400;500;600&family=JetBrains+Mono:wght@400;500&display=swap" rel="stylesheet">
<style>
*, *::before, *::after { margin: 0; padding: 0; box-sizing: border-box; }
:root {
--bg: #FDFCFB;
--slate-900: #0f172a;
--slate-800: #1e293b;
--slate-700: #334155;
--slate-600: #475569;
--slate-500: #64748b;
--slate-400: #94a3b8;
--slate-300: #cbd5e1;
--slate-200: #e2e8f0;
--slate-100: #f1f5f9;
--slate-50: #f8fafc;
--amber-500: #f59e0b;
--amber-600: #d97706;
--amber-700: #b45309;
--amber-50: #fffbeb;
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--emerald-400: #34d399;
--emerald-900: #064e3b;
--emerald-800: #065f46;
--emerald-100: #d1fae5;
--emerald-50: #ecfdf5;
--rose-500: #f43f5e;
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--indigo-600: #4f46e5;
--purple-600: #9333ea;
}
body {
font-family: 'Inter', ui-sans-serif, system-ui, sans-serif;
background: var(--bg);
color: var(--slate-800);
-webkit-font-smoothing: antialiased;
}
.container {
max-width: 1024px;
margin: 0 auto;
padding: 48px 24px 64px;
}
@media (min-width: 768px) { .container { padding: 96px 24px 80px; } }
/* Typography */
.font-serif { font-family: 'Playfair Display', ui-serif, Georgia, serif; }
.font-mono { font-family: 'JetBrains Mono', ui-monospace, monospace; }
/* Header */
header {
border-bottom: 1px solid var(--slate-200);
padding-bottom: 40px;
margin-bottom: 96px;
display: flex;
justify-content: space-between;
align-items: flex-end;
flex-wrap: wrap;
gap: 16px;
}
header h1 {
font-family: 'Playfair Display', serif;
font-size: 36px;
font-weight: 400;
color: var(--slate-900);
line-height: 1.2;
}
header .meta {
font-size: 15px;
font-weight: 300;
color: var(--slate-500);
letter-spacing: 0.04em;
}
/* Sections */
.section { margin-bottom: 128px; }
.section-label {
font-size: 12px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.2em;
color: var(--slate-400);
margin-bottom: 24px;
}
/* Narrative + KPIs */
.summary {
display: grid;
grid-template-columns: 1fr;
gap: 48px;
align-items: start;
}
@media (min-width: 768px) {
.summary { grid-template-columns: 1fr 240px; }
}
.narrative {
font-family: 'Playfair Display', serif;
font-size: 26px;
line-height: 1.45;
color: var(--slate-900);
}
.narrative .highlight {
background: var(--amber-50);
color: var(--amber-700);
padding: 1px 6px;
border-radius: 3px;
}
.kpi-stack {
display: flex;
flex-direction: column;
gap: 32px;
}
@media (min-width: 768px) {
.kpi-stack { border-left: 1px solid var(--slate-200); padding-left: 32px; }
}
.kpi-item .kpi-value {
font-size: 36px;
font-weight: 300;
color: var(--slate-900);
letter-spacing: -0.02em;
}
.kpi-item .kpi-label {
font-size: 10px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.15em;
color: var(--slate-500);
margin-top: 2px;
}
/* Taxonomy bars */
.taxonomy-list { display: flex; flex-direction: column; gap: 20px; }
.tax-row { display: grid; grid-template-columns: 24px 1fr 52px; gap: 12px; align-items: center; }
.tax-rank {
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-400);
text-align: right;
}
.tax-body { display: flex; flex-direction: column; gap: 6px; }
.tax-label { font-size: 14px; font-weight: 500; color: var(--slate-800); }
.tax-bar-track { height: 4px; background: var(--slate-100); border-radius: 100px; overflow: hidden; }
.tax-bar-fill { height: 100%; border-radius: 100px; transition: width 0.6s ease; }
.tax-bar-fill.top { background: var(--amber-500); }
.tax-bar-fill.rest { background: var(--slate-300); }
.tax-pct {
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-500);
text-align: right;
}
.tax-quote {
font-size: 12px;
font-style: italic;
color: var(--slate-500);
margin-top: 2px;
}
/* Evolution timeline */
.evolution-grid {
display: grid;
grid-template-columns: 1fr;
gap: 24px;
}
@media (min-width: 768px) { .evolution-grid { grid-template-columns: repeat(3, 1fr); } }
.evo-card {
background: white;
border: 1px solid var(--slate-200);
border-radius: 16px;
padding: 28px;
}
.evo-card .evo-month {
font-family: 'Playfair Display', serif;
font-size: 20px;
color: var(--slate-900);
margin-bottom: 4px;
}
.evo-card .evo-theme {
font-size: 12px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 0.12em;
margin-bottom: 16px;
}
.evo-card .evo-desc {
font-size: 14px;
color: var(--slate-600);
line-height: 1.6;
}
.evo-card .evo-stat {
margin-top: 16px;
padding-top: 16px;
border-top: 1px solid var(--slate-100);
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-500);
}
.evo-jan .evo-theme { color: var(--slate-600); }
.evo-feb .evo-theme { color: var(--amber-600); }
.evo-mar .evo-theme { color: var(--indigo-600); }
/* Quality comparison */
.quality-grid {
display: grid;
grid-template-columns: 1fr;
gap: 24px;
}
@media (min-width: 768px) { .quality-grid { grid-template-columns: 1fr 1fr; } }
.q-card {
border-radius: 24px;
padding: 36px;
}
.q-card.good {
background: color-mix(in srgb, var(--emerald-50) 50%, transparent);
border: 1px solid var(--emerald-100);
}
.q-card.bad {
background: color-mix(in srgb, var(--rose-50) 50%, transparent);
border: 1px solid var(--rose-100);
}
.q-card .q-icon { font-size: 20px; margin-bottom: 12px; }
.q-card .q-title {
font-family: 'Playfair Display', serif;
font-size: 22px;
margin-bottom: 20px;
}
.q-card.good .q-title { color: var(--emerald-900); }
.q-card.bad .q-title { color: var(--rose-900); }
.q-list { list-style: none; display: flex; flex-direction: column; gap: 14px; }
.q-list li {
display: flex;
align-items: flex-start;
gap: 10px;
font-size: 14px;
line-height: 1.6;
}
.q-card.good .q-list li { color: color-mix(in srgb, var(--emerald-800) 90%, transparent); }
.q-card.bad .q-list li { color: color-mix(in srgb, var(--rose-800) 90%, transparent); }
.q-dot {
width: 6px;
height: 6px;
border-radius: 50%;
flex-shrink: 0;
margin-top: 7px;
}
.q-card.good .q-dot { background: var(--emerald-400); }
.q-card.bad .q-dot { background: var(--rose-400); }
/* Phrases */
.phrases-grid {
display: grid;
grid-template-columns: repeat(2, 1fr);
gap: 12px;
}
@media (min-width: 768px) { .phrases-grid { grid-template-columns: repeat(3, 1fr); } }
.phrase-chip {
background: white;
border: 1px solid var(--slate-200);
border-radius: 12px;
padding: 14px 16px;
display: flex;
justify-content: space-between;
align-items: center;
gap: 8px;
}
.phrase-text {
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-700);
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
}
.phrase-count {
font-family: 'JetBrains Mono', monospace;
font-size: 11px;
color: var(--slate-400);
flex-shrink: 0;
}
/* Dark action panel */
.action-panel {
background: var(--slate-900);
color: white;
border-radius: 24px;
padding: 40px;
box-shadow: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
}
@media (min-width: 768px) { .action-panel { padding: 56px; } }
.action-panel .section-label { color: var(--slate-500); }
.action-panel .ap-intro {
font-family: 'Playfair Display', serif;
font-size: 22px;
color: white;
line-height: 1.4;
margin-bottom: 32px;
max-width: 640px;
}
.prompt-block {
background: color-mix(in srgb, var(--slate-800) 80%, transparent);
border: 1px solid color-mix(in srgb, var(--slate-700) 50%, transparent);
border-radius: 16px;
overflow: hidden;
}
.prompt-header {
display: flex;
justify-content: space-between;
align-items: center;
padding: 12px 20px;
border-bottom: 1px solid color-mix(in srgb, var(--slate-700) 30%, transparent);
}
.prompt-header-label {
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-400);
display: flex;
align-items: center;
gap: 8px;
}
.prompt-header-label svg { width: 14px; height: 14px; }
.copy-btn {
background: none;
border: none;
font-family: 'JetBrains Mono', monospace;
font-size: 12px;
color: var(--slate-400);
cursor: pointer;
display: flex;
align-items: center;
gap: 6px;
transition: color 0.2s;
}
.copy-btn:hover { color: white; }
.copy-btn.copied { color: var(--emerald-400); }
.prompt-body {
padding: 20px;
max-height: 480px;
overflow-y: auto;
}
.prompt-body pre {
font-family: 'JetBrains Mono', monospace;
font-size: 13px;
line-height: 1.7;
color: color-mix(in srgb, var(--amber-200) 90%, transparent);
white-space: pre-wrap;
word-break: break-word;
}
.prompt-body pre .comment {
color: var(--slate-500);
}
/* Glow card */
.glow-wrap {
position: relative;
margin-top: 48px;
}
.glow-bg {
position: absolute;
inset: -2px;
background: linear-gradient(135deg, var(--indigo-500), var(--purple-600));
border-radius: 26px;
opacity: 0.15;
filter: blur(16px);
transition: opacity 0.5s;
}
.glow-wrap:hover .glow-bg { opacity: 0.25; }
.glow-card {
position: relative;
background: white;
border: 1px solid var(--slate-200);
border-radius: 24px;
padding: 32px 36px;
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
gap: 20px;
}
.glow-card .gc-text {
font-family: 'Playfair Display', serif;
font-size: 18px;
font-weight: 500;
color: var(--slate-900);
line-height: 1.5;
max-width: 640px;
}
.glow-card .gc-text em {
font-style: italic;
color: var(--indigo-600);
}
/* Footer */
footer {
border-top: 1px solid var(--slate-200);
padding-top: 48px;
margin-top: 0;
text-align: center;
}
footer p {
font-family: 'Playfair Display', serif;
font-style: italic;
font-size: 15px;
color: var(--slate-400);
}
/* Scrollbar in dark code block */
.prompt-body::-webkit-scrollbar { width: 6px; }
.prompt-body::-webkit-scrollbar-track { background: transparent; }
.prompt-body::-webkit-scrollbar-thumb { background: var(--slate-700); border-radius: 3px; }
</style>
</head>
<body>
<div class="container">
<header>
<div>
<h1>What 370 Files Reveal About<br>How You Plan</h1>
<div class="meta" style="margin-top: 8px;">backnotprop/plannotator &middot; Jan 7 &ndash; Mar 18, 2026</div>
</div>
<div class="meta" style="text-align: right;">
<span class="font-mono" style="font-size: 12px;">202 denials &middot; 168 annotations &middot; 71 days</span>
</div>
</header>
<!-- 1. Narrative + KPIs -->
<div class="section">
<div class="section-label">1. The story in the data</div>
<div class="summary">
<div class="narrative">
Across 71 days you denied or revised <span class="highlight">202 plans</span> before any code was written. The single most common reason&mdash;appearing in 1 out of 4 denials&mdash;was the same: the agent jumped to implementation without telling you <em>what</em> it was building, <em>why</em>, or <em>how</em>. Missing narrative. Missing context. Missing the story. Your expectations evolved from &ldquo;does it work?&rdquo; in January to &ldquo;tell me the story and be confident&rdquo; by March.
</div>
<div class="kpi-stack">
<div class="kpi-item">
<div class="kpi-value">25.7%</div>
<div class="kpi-label">Denials for missing narrative</div>
</div>
<div class="kpi-item">
<div class="kpi-value">50%</div>
<div class="kpi-label">Plans revised before coding</div>
</div>
<div class="kpi-item">
<div class="kpi-value">12</div>
<div class="kpi-label">Distinct denial categories</div>
</div>
</div>
</div>
</div>
<!-- 2. Denial Taxonomy -->
<div class="section">
<div class="section-label">2. Why plans get denied</div>
<div class="taxonomy-list">
<div class="tax-row">
<span class="tax-rank">1</span>
<div class="tax-body">
<span class="tax-label">Missing Narrative / Overview</span>
<div class="tax-bar-track"><div class="tax-bar-fill top" style="width: 100%"></div></div>
<span class="tax-quote">"This plan is denied without narrative detail and rationales."</span>
</div>
<span class="tax-pct">25.7%</span>
</div>
<div class="tax-row">
<span class="tax-rank">2</span>
<div class="tax-body">
<span class="tax-label">Clarification Needed</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 65%"></div></div>
<span class="tax-quote">"What does this Mean???"</span>
</div>
<span class="tax-pct">16.8%</span>
</div>
<div class="tax-row">
<span class="tax-rank">3</span>
<div class="tax-body">
<span class="tax-label">Testing / Procedural</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 54%"></div></div>
<span class="tax-quote">"I'm denying so you can create a diff."</span>
</div>
<span class="tax-pct">13.9%</span>
</div>
<div class="tax-row">
<span class="tax-rank">4</span>
<div class="tax-body">
<span class="tax-label">Wrong Approach / Over-Engineered</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 37%"></div></div>
<span class="tax-quote">"Why are we doing difficult shit here? I want a hover experience."</span>
</div>
<span class="tax-pct">9.4%</span>
</div>
<div class="tax-row">
<span class="tax-rank">5</span>
<div class="tax-body">
<span class="tax-label">Process Requirement</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 31%"></div></div>
<span class="tax-quote">"Make sure you feature branch."</span>
</div>
<span class="tax-pct">7.9%</span>
</div>
<div class="tax-row">
<span class="tax-rank">6</span>
<div class="tax-body">
<span class="tax-label">Confidence / Risk Check</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 29%"></div></div>
<span class="tax-quote">"Take a step back, breathe, make sure we're not being irrational."</span>
</div>
<span class="tax-pct">7.4%</span>
</div>
<div class="tax-row">
<span class="tax-rank">7</span>
<div class="tax-body">
<span class="tax-label">Content Removal</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 27%"></div></div>
<span class="tax-quote">"I don't want this in the plan."</span>
</div>
<span class="tax-pct">6.9%</span>
</div>
<div class="tax-row">
<span class="tax-rank">8</span>
<div class="tax-body">
<span class="tax-label">Implementation Bug Found</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 23%"></div></div>
</div>
<span class="tax-pct">5.9%</span>
</div>
<div class="tax-row">
<span class="tax-rank">9</span>
<div class="tax-body">
<span class="tax-label">Design / UX Issue</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 21%"></div></div>
</div>
<span class="tax-pct">5.4%</span>
</div>
<div class="tax-row">
<span class="tax-rank">10</span>
<div class="tax-body">
<span class="tax-label">Naming / Terminology</span>
<div class="tax-bar-track"><div class="tax-bar-fill rest" style="width: 16%"></div></div>
<span class="tax-quote">"Why do you keep calling it Simplified????"</span>
</div>
<span class="tax-pct">4.0%</span>
</div>
</div>
</div>
<!-- 3. Evolution -->
<div class="section">
<div class="section-label">3. How your expectations evolved</div>
<div class="evolution-grid">
<div class="evo-card evo-jan">
<div class="evo-month">January</div>
<div class="evo-theme">"Does it work?"</div>
<div class="evo-desc">Bug-hunting phase. You were hands-on testing View Logs, iterating on session scoping heuristics. 60% of denials were implementation bugs and verification failures. No mention of &ldquo;narrative&rdquo; or &ldquo;overview&rdquo; yet.</div>
<div class="evo-stat">26 denials &middot; 0 narrative requests</div>
</div>
<div class="evo-card evo-feb">
<div class="evo-month">February</div>
<div class="evo-theme">"Follow the process"</div>
<div class="evo-desc">Process gates emerged: feature branches, Linear tickets, pull main. 40% of denials were procedural (diff testing). UX polish intensified. The first narrative demands appeared: &ldquo;I want a narrative under each section.&rdquo;</div>
<div class="evo-stat">48 denials &middot; 6 narrative requests</div>
</div>
<div class="evo-card evo-mar">
<div class="evo-month">March</div>
<div class="evo-theme">"Tell me the story"</div>
<div class="evo-desc">Narrative became the #1 gate. You created a &ldquo;Missing overview&rdquo; label and applied it systematically. Confidence checks became standard. You began telling agents to &ldquo;take a step back, breathe, and analyze.&rdquo;</div>
<div class="evo-stat">128 denials &middot; 25+ narrative requests</div>
</div>
</div>
</div>
<!-- 4. Quality comparison -->
<div class="section">
<div class="section-label">4. What works vs. what doesn't</div>
<div class="quality-grid">
<div class="q-card good">
<div class="q-icon">&#10003;</div>
<div class="q-title">What approved plans do</div>
<ul class="q-list">
<li><span class="q-dot"></span>Lead with a narrative overview: what exists, what changes, why</li>
<li><span class="q-dot"></span>State confidence and identify risks proactively</li>
<li><span class="q-dot"></span>Reference existing codebase patterns before proposing new code</li>
<li><span class="q-dot"></span>Use explicit, transparent naming (not euphemisms)</li>
<li><span class="q-dot"></span>Break large work into phases with evaluation gates</li>
<li><span class="q-dot"></span>Include example output for user-facing changes</li>
<li><span class="q-dot"></span>Specify feature branch and ticket creation steps</li>
</ul>
</div>
<div class="q-card bad">
<div class="q-icon">&#10007;</div>
<div class="q-title">What agents keep getting wrong</div>
<ul class="q-list">
<li><span class="q-dot"></span>Jump to implementation steps without narrative context</li>
<li><span class="q-dot"></span>Over-engineer: Shift+Click when hover works, MCP tool when a README suffices</li>
<li><span class="q-dot"></span>Introduce new code for things the codebase already solves</li>
<li><span class="q-dot"></span>Propose work on top of failing lint/type checks</li>
<li><span class="q-dot"></span>Use vague or euphemistic naming (&ldquo;Accept&rdquo; instead of &ldquo;Git Add&rdquo;)</li>
<li><span class="q-dot"></span>Wait to be asked for confidence instead of stating it</li>
<li><span class="q-dot"></span>Rush to modify instead of reporting what they see</li>
</ul>
</div>
</div>
</div>
<!-- 5. The actionable output -->
<div class="section">
<div class="section-label">5. The actionable output</div>
<div class="narrative" style="margin-bottom: 32px;">
The analysis produced <span class="highlight">17 specific prompt instructions</span> that, if embedded in a planning prompt, would address ~70% of all denial reasons. The biggest three:
</div>
<div style="display: flex; flex-direction: column; gap: 20px;">
<div style="display: flex; gap: 16px; align-items: flex-start;">
<span class="font-mono" style="font-size: 24px; font-weight: 300; color: var(--amber-500); flex-shrink: 0; width: 32px; text-align: right;">1</span>
<div>
<div style="font-size: 17px; font-weight: 500; color: var(--slate-900); margin-bottom: 4px;">Every plan MUST start with a Solution Overview</div>
<div style="font-size: 14px; color: var(--slate-600); line-height: 1.5;">What exists, what changes, why, how. This alone addresses 1 in 4 denials.</div>
</div>
</div>
<div style="display: flex; gap: 16px; align-items: flex-start;">
<span class="font-mono" style="font-size: 24px; font-weight: 300; color: var(--amber-500); flex-shrink: 0; width: 32px; text-align: right;">2</span>
<div>
<div style="font-size: 17px; font-weight: 500; color: var(--slate-900); margin-bottom: 4px;">End every plan with a Confidence Assessment</div>
<div style="font-size: 14px; color: var(--slate-600); line-height: 1.5;">Don&rsquo;t wait to be asked. State your confidence, identify risks, flag uncertainties.</div>
</div>
</div>
<div style="display: flex; gap: 16px; align-items: flex-start;">
<span class="font-mono" style="font-size: 24px; font-weight: 300; color: var(--amber-500); flex-shrink: 0; width: 32px; text-align: right;">3</span>
<div>
<div style="font-size: 17px; font-weight: 500; color: var(--slate-900); margin-bottom: 4px;">Search for existing patterns before proposing new code</div>
<div style="font-size: 14px; color: var(--slate-600); line-height: 1.5;">Explicitly state what you found in the codebase. Prefer reuse over new implementation.</div>
</div>
</div>
</div>
</div>
<!-- 6. Recurring phrases -->
<div class="section">
<div class="section-label">6. Your most-used phrases</div>
<div class="phrases-grid">
<div class="phrase-chip"><span class="phrase-text">"narrative"</span><span class="phrase-count">50+</span></div>
<div class="phrase-chip"><span class="phrase-text">"I don't want this in the plan"</span><span class="phrase-count">10</span></div>
<div class="phrase-chip"><span class="phrase-text">"feature branch"</span><span class="phrase-count">8+</span></div>
<div class="phrase-chip"><span class="phrase-text">"confidence"</span><span class="phrase-count">8+</span></div>
<div class="phrase-chip"><span class="phrase-text">"Missing overview"</span><span class="phrase-count">14</span></div>
<div class="phrase-chip"><span class="phrase-text">"front-end design skill"</span><span class="phrase-count">16</span></div>
<div class="phrase-chip"><span class="phrase-text">"separation of concerns"</span><span class="phrase-count">6</span></div>
<div class="phrase-chip"><span class="phrase-text">"Take a step back, breathe"</span><span class="phrase-count">6</span></div>
<div class="phrase-chip"><span class="phrase-text">"how does this work"</span><span class="phrase-count">5+</span></div>
<div class="phrase-chip"><span class="phrase-text">"what the fuck"</span><span class="phrase-count">4</span></div>
<div class="phrase-chip"><span class="phrase-text">"create a ticket"</span><span class="phrase-count">4+</span></div>
<div class="phrase-chip"><span class="phrase-text">"reusable"</span><span class="phrase-count">19+</span></div>
</div>
</div>
<!-- 7. Corrective Prompt -->
<div class="section" style="margin-bottom: 64px;">
<div class="action-panel">
<div class="section-label">7. The corrective prompt</div>
<div class="ap-intro">
These 17 instructions were extracted directly from your denial patterns. Embedding them in a planning prompt would address approximately 70% of all denial reasons.
</div>
<div class="prompt-block">
<div class="prompt-header">
<span class="prompt-header-label">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="4 17 10 11 4 5"></polyline><line x1="12" y1="19" x2="20" y2="19"></line></svg>
planning-instructions.md
</span>
<button class="copy-btn" onclick="copyPrompt(this)">
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Copy
</button>
</div>
<div class="prompt-body">
<pre id="prompt-content"><span class="comment"># Planning Instructions
# Derived from 370 files of denial & annotation analysis</span>
1. STRUCTURE: Every plan MUST begin with a "Solution Overview"
containing 2-3 paragraphs of narrative prose explaining:
- What exists today (current state)
- What will change and why
- How it will be built (approach summary)
Do NOT skip this. Do NOT replace it with bullet points.
2. NARRATIVE: Every major section must include a rationale
paragraph — not just what will be done, but WHY this
approach was chosen over alternatives.
3. FEATURE BRANCH: Always specify implementation will occur
on a feature branch. State the branch name. Never plan
to work directly on main.
4. EXISTING PATTERNS: Before proposing any new implementation,
search the codebase for existing patterns that solve the
same problem. Explicitly state what you found and whether
you will reuse it. Prefer reuse over new code.
5. CONFIDENCE STATEMENT: End the plan with a "Confidence
Assessment" section. State your confidence level, identify
risks or edge cases, and note uncertainties. Do not wait
to be asked.
6. PHASING: For plans with more than 3 steps, break them into
numbered phases. After each phase, note "Pause for
evaluation" so the reviewer can assess before proceeding.
7. ISSUE TRACKING: If the project uses Linear or GitHub Issues,
include a step to create relevant tickets BEFORE
implementation. Backlog items should be separate tickets.
8. SIMPLICITY: Choose the simplest approach that meets
requirements. Do not introduce modifier keys when hover
works. Do not build a framework when a README suffices.
9. NAMING: Use explicit, transparent names for user-facing
features. Do not euphemize Git operations ("Git Add"
not "Accept"). Match existing product naming conventions.
10. CODE QUALITY: State that implementation will follow clean
code principles: modular architecture, separation of
concerns, no circumventing lint or type checks.
11. CLEAN FOUNDATION: If the codebase has failing lint or type
checks, address these BEFORE proposing new features. State
the current CI/CD state.
12. PRIVACY: For features involving data storage or sharing,
explicitly state privacy guarantees. Require user
confirmation before storing data.
13. EXAMPLES: When the plan involves user-facing output or UI,
include an example of what it will look like.
14. FOCUSED SCOPE: Do not include sections that are obvious,
boilerplate, or previously asked to be removed. Keep the
plan focused rather than comprehensive.
15. DESIGN SKILL: For any frontend/UI work, invoke the
front-end design skill to validate the approach. Note
this invocation explicitly in the plan.
16. VERIFICATION STEP: For refactors or multi-file changes,
include a verification step with line-by-line comparison
of affected code paths.
17. DELIBERATION: If the plan involves a dramatic shift, state
that you have re-evaluated the approach, traced through
affected files mentally, and are confident in the plan.
Do not rush.</pre>
</div>
</div>
<div class="glow-wrap">
<div class="glow-bg"></div>
<div class="glow-card">
<div class="gc-text">
These instructions are yours &mdash; derived from <em>your feedback, your language, your standards</em>. Copy them into your planning prompt and watch the deny rate drop.
</div>
</div>
</div>
</div>
</div>
<footer>
<p>Analysis of 202 denied plans and 168 annotation files from the Plannotator archive.</p>
</footer>
</div>
<script>
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+39
View File
@@ -224,6 +224,45 @@ echo Address the annotation feedback above. The user has reviewed your last mess
echo Installed /plannotator-last command to !CLAUDE_COMMANDS_DIR!\plannotator-last.md
REM Install skills (requires git)
where git >nul 2>&1
if !ERRORLEVEL! equ 0 (
if defined CLAUDE_CONFIG_DIR (
set "CLAUDE_SKILLS_DIR=%CLAUDE_CONFIG_DIR%\skills"
) else (
set "CLAUDE_SKILLS_DIR=%USERPROFILE%\.claude\skills"
)
if defined XDG_CONFIG_HOME (
set "AGENTS_SKILLS_DIR=%XDG_CONFIG_HOME%\agents\skills"
) else (
set "AGENTS_SKILLS_DIR=%USERPROFILE%\.config\agents\skills"
)
set "SKILLS_TMP=%TEMP%\plannotator-skills-%RANDOM%"
mkdir "!SKILLS_TMP!" >nul 2>&1
git clone --depth 1 --filter=blob:none --sparse "https://github.com/!REPO!.git" --branch "!TAG!" "!SKILLS_TMP!\repo" >nul 2>&1
if !ERRORLEVEL! equ 0 (
pushd "!SKILLS_TMP!\repo"
git sparse-checkout set apps/skills >nul 2>&1
if exist "apps\skills" (
if not exist "!CLAUDE_SKILLS_DIR!" mkdir "!CLAUDE_SKILLS_DIR!"
if not exist "!AGENTS_SKILLS_DIR!" mkdir "!AGENTS_SKILLS_DIR!"
xcopy /s /y /q "apps\skills\*" "!CLAUDE_SKILLS_DIR!\" >nul 2>&1
xcopy /s /y /q "apps\skills\*" "!AGENTS_SKILLS_DIR!\" >nul 2>&1
echo Installed skills to !CLAUDE_SKILLS_DIR!\ and !AGENTS_SKILLS_DIR!\
)
popd
) else (
echo Skipping skills install ^(git sparse-checkout failed^)
)
rmdir /s /q "!SKILLS_TMP!" >nul 2>&1
) else (
echo Skipping skills install ^(git not found^)
)
echo.
echo Test the install:
echo echo {"tool_input":{"plan":"# Test Plan\\n\\nHello world"}} ^| plannotator
+33
View File
@@ -217,6 +217,39 @@ description: Annotate the last assistant message
Write-Host "Installed /plannotator-last command to $opencodeCommandsDir\plannotator-last.md"
# Install skills (requires git)
if (Get-Command git -ErrorAction SilentlyContinue) {
$claudeSkillsDir = if ($env:CLAUDE_CONFIG_DIR) { "$env:CLAUDE_CONFIG_DIR\skills" } else { "$env:USERPROFILE\.claude\skills" }
$agentsSkillsDir = if ($env:XDG_CONFIG_HOME) { "$env:XDG_CONFIG_HOME\agents\skills" } else { "$env:USERPROFILE\.config\agents\skills" }
$skillsTmp = Join-Path ([System.IO.Path]::GetTempPath()) "plannotator-skills-$(Get-Random)"
New-Item -ItemType Directory -Force -Path $skillsTmp | Out-Null
try {
git clone --depth 1 --filter=blob:none --sparse "https://github.com/$repo.git" --branch $latestTag "$skillsTmp\repo" 2>$null
Push-Location "$skillsTmp\repo"
git sparse-checkout set apps/skills 2>$null
if (Test-Path "apps\skills") {
$items = Get-ChildItem "apps\skills" -ErrorAction SilentlyContinue
if ($items) {
New-Item -ItemType Directory -Force -Path $claudeSkillsDir | Out-Null
New-Item -ItemType Directory -Force -Path $agentsSkillsDir | Out-Null
Copy-Item -Recurse -Force "apps\skills\*" $claudeSkillsDir
Copy-Item -Recurse -Force "apps\skills\*" $agentsSkillsDir
Write-Host "Installed skills to $claudeSkillsDir\ and $agentsSkillsDir\"
}
}
Pop-Location
} catch {
Write-Host "Skipping skills install (git sparse-checkout failed)"
}
Remove-Item -Recurse -Force $skillsTmp -ErrorAction SilentlyContinue
} else {
Write-Host "Skipping skills install (git not found)"
}
Write-Host ""
Write-Host "=========================================="
Write-Host " OPENCODE USERS"
+27
View File
@@ -213,6 +213,33 @@ COMMAND_EOF
echo "Installed /plannotator-last command to ${OPENCODE_COMMANDS_DIR}/plannotator-last.md"
# Install skills (requires git)
if command -v git &>/dev/null; then
CLAUDE_SKILLS_DIR="${CLAUDE_CONFIG_DIR:-$HOME/.claude}/skills"
AGENTS_SKILLS_DIR="${XDG_CONFIG_HOME:-$HOME/.config}/agents/skills"
skills_tmp=$(mktemp -d)
if git clone --depth 1 --filter=blob:none --sparse \
"https://github.com/${REPO}.git" --branch "$latest_tag" "$skills_tmp/repo" 2>/dev/null && \
cd "$skills_tmp/repo" && git sparse-checkout set apps/skills 2>/dev/null; then
if [ -d "apps/skills" ] && [ "$(ls -A apps/skills 2>/dev/null)" ]; then
mkdir -p "$CLAUDE_SKILLS_DIR" "$AGENTS_SKILLS_DIR"
cp -r apps/skills/* "$CLAUDE_SKILLS_DIR/"
cp -r apps/skills/* "$AGENTS_SKILLS_DIR/"
echo "Installed skills to ${CLAUDE_SKILLS_DIR}/ and ${AGENTS_SKILLS_DIR}/"
fi
cd - >/dev/null
else
echo "Skipping skills install (git sparse-checkout failed)"
fi
rm -rf "$skills_tmp"
else
echo "Skipping skills install (git not found)"
fi
echo ""
echo "=========================================="
echo " OPENCODE USERS"
+24
View File
@@ -52,6 +52,14 @@ describe("install.sh", () => {
expect(script).toContain('"command".*plannotator');
});
test("installs skills via git sparse-checkout", () => {
expect(script).toContain("git clone --depth 1 --filter=blob:none --sparse");
expect(script).toContain("git sparse-checkout set apps/skills");
expect(script).toContain("CLAUDE_SKILLS_DIR");
expect(script).toContain("AGENTS_SKILLS_DIR");
expect(script).toContain('Skipping skills install (git not found)');
});
test("installs slash commands for Claude Code and OpenCode", () => {
expect(script).toContain("plannotator-review.md");
expect(script).toContain("plannotator-annotate.md");
@@ -97,6 +105,14 @@ describe("install.ps1", () => {
expect(script).toContain("DUPLICATE HOOK DETECTED");
});
test("installs skills via git sparse-checkout", () => {
expect(script).toContain("git clone --depth 1 --filter=blob:none --sparse");
expect(script).toContain("git sparse-checkout set apps/skills");
expect(script).toContain("claudeSkillsDir");
expect(script).toContain("agentsSkillsDir");
expect(script).toContain('Skipping skills install (git not found)');
});
test("installs slash commands", () => {
expect(script).toContain("plannotator-review.md");
expect(script).toContain("plannotator-annotate.md");
@@ -137,6 +153,14 @@ describe("install.cmd", () => {
expect(script).toContain("DUPLICATE HOOK DETECTED");
});
test("installs skills via git sparse-checkout", () => {
expect(script).toContain("git clone --depth 1 --filter=blob:none --sparse");
expect(script).toContain("git sparse-checkout set apps/skills");
expect(script).toContain("CLAUDE_SKILLS_DIR");
expect(script).toContain("AGENTS_SKILLS_DIR");
expect(script).toContain("Skipping skills install");
});
test("installs slash commands", () => {
expect(script).toContain("plannotator-review.md");
expect(script).toContain("plannotator-annotate.md");