diff --git a/SKILL.md b/SKILL.md index e83b59f..76eb00d 100644 --- a/SKILL.md +++ b/SKILL.md @@ -29,6 +29,8 @@ AI writing has a recognizable smell. It's not about any single word or trick. It **Your job is not to dumb the writing down.** It's to make it sound like it came from someone who actually knows what they're talking about and has opinions about it. +**Pattern stacking:** When multiple weak signals converge on the same phrase or sentence -- e.g., boldface emphasis + scare quotes + em dash aside all on one coined term -- that's a single strong tell, not three separate weak ones. Consolidate overlapping patterns into one finding. Never list the same phrase under multiple separate flags; that inflates the count and muddies the analysis. + --- ## The Editing Process @@ -103,17 +105,19 @@ Several grammar-level tics give AI away even when the vocabulary is clean. #### Copula avoidance -AI substitutes elaborate constructions for simple "is"/"are"/"has." +AI substitutes elaborate constructions for simple "is"/"are"/"has." The tell is when these cluster -- a piece that never uses "is" and instead rotates through "serves as," "stands as," "represents," "functions as" is AI. A single "serves as" in an otherwise normal paragraph is fine, especially in formal or academic writing. -- "serves as" / "stands as" / "represents" -> "is" -- "boasts" / "features" / "offers" -> "has" +- "serves as" / "stands as" / "represents" -> "is" (when clustering) +- "boasts" / "features" / "offers" -> "has" (when clustering) -**Before:** +**Before (clustering -- AI tell):** > Gallery 825 serves as LAAA's exhibition space. The gallery features four rooms and boasts 3,000 square feet. **After:** > Gallery 825 is LAAA's exhibition space. The gallery has four rooms totaling 3,000 square feet. +**Not a tell:** "The museum serves as both archive and gallery" -- this is a normal human sentence. + #### Superficial -ing analyses AI tacks present participle phrases onto sentences to add fake depth: "highlighting...", "underscoring...", "emphasizing...", "reflecting...", "symbolizing...", "showcasing...", "contributing to...", "fostering..." @@ -122,15 +126,15 @@ AI tacks present participle phrases onto sentences to add fake depth: "highlight #### Negative parallelisms -"Not only... but..." and "It's not just about X, it's about Y" -- fine once, AI uses it 5-10 times per piece. +"Not only... but..." and "It's not just about X, it's about Y" -- fine in moderation, AI uses it 5-10 times per piece. The tell is density relative to piece length, not an absolute count. -**Fix:** Use once max. State the point directly the rest of the time. +**Fix:** In a short piece (under 1000 words), once is plenty. In a longer piece, twice is fine. The issue is when it becomes a structural crutch. #### Rule of three overuse -AI forces ideas into groups of three: "innovation, inspiration, and insights." +AI forces ideas into groups of three where the third item is clearly padding: "innovation, inspiration, and insights." Tricolons are one of the oldest rhetorical devices in human writing ("life, liberty, and the pursuit of happiness"), so don't flag every group of three -- flag groups where the third item adds nothing or is a near-synonym of the first two. -**Fix:** Use the natural number of items. Two is fine. Four is fine. Don't force three. +**Fix:** If the third item pulls its weight, leave it. If it's padding, cut to two or restructure. #### Synonym cycling (elegant variation) @@ -170,9 +174,12 @@ AI writes in a metronomic cadence. Medium sentence. Medium sentence. Medium sent #### Em dash overuse -AI uses em dashes more than humans, mimicking "punchy" sales writing. One em dash per 3-4 paragraphs is human frequency. +AI uses em dashes to inject dramatic asides and parenthetical explanations. The tell is both frequency and function. Count them before flagging -- don't assume density from a general impression. -**Fix:** Use commas or periods. Restructure the sentence. +- **Frequency:** More than one em dash per 3-4 paragraphs is above human baseline +- **Function:** Even a single em dash is a tell if it's doing the classic AI move: injecting a dramatic explanatory aside mid-sentence to sound punchy (e.g., "the system -- designed to handle millions of requests -- struggled under load") + +**Fix:** Use commas or periods. Restructure the sentence. When reviewing, actually count em dashes before claiming overuse. #### Boldface overuse @@ -194,7 +201,7 @@ Lists where every item starts with a bolded header followed by a colon. #### Title case in headings -AI capitalizes all main words. Use sentence case unless the style guide specifically requires title case. +AI defaults to title case for all headings. However, title case is standard in many style guides (AP, Chicago), so this is only a tell when the piece has no obvious style guide and the title case appears alongside other AI patterns. Don't flag title case in isolation -- it's a weak signal at best. #### Emojis @@ -202,7 +209,7 @@ AI decorates headings or bullet points with emojis. Remove them. #### Curly quotation marks -ChatGPT uses curly quotes. Replace with straight quotes for consistency with most web/code contexts. +ChatGPT uses curly quotes (\u201c \u201d). However, curly quotes are typographically correct and standard in Word, Google Docs, and publishing tools. Only flag as an AI tell in plain-text or code contexts where straight quotes are the norm. In formatted content, curly quotes are expected. --- @@ -250,10 +257,12 @@ Text meant as chatbot correspondence gets pasted as content: "I hope this helps! #### Knowledge-cutoff disclaimers -"As of [date]," "While specific details are limited...," "Based on available information..." +"While specific details are limited...," "Based on available information..." **Fix:** Find actual sources or delete the claim. +**Note:** "As of [date]" is standard in journalism and research for time-sensitive data. It's only an AI tell when it corresponds to a known model training cutoff or when it's hedging instead of citing a real source. Don't flag it in data-driven writing where the date adds genuine context. + #### Sycophantic tone "Great question! You're absolutely right that this is a complex topic." @@ -384,6 +393,9 @@ When reviewing without rewriting (if asked): 1. Flag specific passages that read as AI-generated 2. Explain which pattern each one triggers 3. Suggest concrete alternatives +4. Consolidate overlapping flags -- if multiple patterns hit the same phrase, report it once as a stacking pattern rather than padding the count with separate entries +5. Verify quantitative claims before making them (e.g., actually count em dashes, actually count scare-quoted terms) +6. Check whether flagged patterns have a non-AI explanation (e.g., a table has three rows because there are three real items, not because AI forced a triad) --- diff --git a/references/ai-tells.md b/references/ai-tells.md index 7190024..c07e972 100644 --- a/references/ai-tells.md +++ b/references/ai-tells.md @@ -126,7 +126,7 @@ Fine alone, but AI uses these in combination. Three or more in one piece is a te ### Knowledge-Cutoff Disclaimers -- "As of [date]..." -> (delete or find current source) +- "As of [date]..." -> Only a tell when it corresponds to a model training cutoff or hedges instead of citing. Normal in journalism for time-sensitive data. - "While specific details are limited..." -> (delete or find source) - "Based on available information..." -> (delete) @@ -152,7 +152,7 @@ Words and phrases that puff up importance beyond what the content warrants. ### Copula Avoidance -AI substitutes elaborate verbs for "is"/"are"/"has": +AI substitutes elaborate verbs for "is"/"are"/"has." The tell is when these cluster -- a piece that never uses "is" is suspicious. A single "serves as" in formal writing is normal: | AI Construction | Human Alternative | |-|-| @@ -184,11 +184,11 @@ AI tacks participle phrases onto sentences for fake depth: "Not only... but also..." and "It's not just about X, it's about Y." -Fine once per piece. AI uses it 5-10 times. +Fine in moderation. AI uses it 5-10 times per piece. The tell is density relative to length, not an absolute count. ### Rule of Three -AI forces ideas into groups of three to appear comprehensive. Use the natural number of items. +AI forces ideas into groups of three where the third item is padding. Tricolons are a natural rhetorical device -- only flag when the third item adds nothing or is a near-synonym of the first two. ### Synonym Cycling @@ -226,11 +226,14 @@ AI makes every bullet point the same grammatical structure and similar length. **Fix:** End with one strong statement, not a perfectly balanced assessment. -### The Em-Dash Epidemic +### Em Dash Usage -AI uses em dashes constantly, often multiple times per paragraph. +The tell is both frequency and function. Count before flagging -- don't assume density from a general impression. -**Fix:** Use periods. Use commas. One em dash per 3-4 paragraphs is human frequency. +- **Frequency:** More than one em dash per 3-4 paragraphs is above human baseline +- **Function:** Even a single em dash is a tell if it's doing the classic AI move: injecting a dramatic explanatory aside mid-sentence (e.g., "the system -- designed to handle millions of requests -- struggled under load") + +**Fix:** Use periods. Use commas. Actually count em dashes before claiming overuse. --- @@ -263,7 +266,7 @@ Score the piece on these dimensions. 5+ hits = likely AI-generated: - [ ] Has "It's worth noting" or similar filler phrases - [ ] Every section follows the same structure - [ ] "Not X, but Y" appears more than twice -- [ ] Em dashes appear more than once per paragraph +- [ ] Em dashes appear more than once per 3-4 paragraphs, or a single em dash injects a dramatic aside - [ ] No sentences under 8 words - [ ] No informal or colloquial language anywhere - [ ] Conclusion is perfectly balanced (good news/bad news/inspiring close)