Hedge Detector
SkillAI & modelsClassifies every hedge in a substacker draft as either a precision hedge (keep — "n=1 may not replicate", "I do not know") or an epistemic-weakness hedge (flag — "I think", "perhaps", "arguably", "it could be argued"). Only flags weakness hedges; suggests either a commit (remove hedge, take position) or a specific hedge (name the uncertainty). Use when a draft feels wishy-washy or when a cluster of modal verbs appears. Trigger keywords — hedging, I think, perhaps, arguably, uncertainty, weak claim, wishy-washy.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Hedge Detector skill
What this skill tells your AI
The instructions your AI receives, as published by lyndonkl/claude in skills/hedge-detector/SKILL.md and read by ahel’s review.
Table of Contents
- Precision vs weakness
- Workflow
- Worked example
- Guardrails
Related skills: Called by the Editor in the voice pass. Complements voice-check (which flags "I think" as a don't-list phrase when used as primary hedge). This skill does the finer classification.
Precision vs weakness
Precision hedge (KEEP): scope-naming, sample-size-caveat, specific-uncertainty.
- "I do not know" (full sentence) — writer's signature.
- "I am not claiming…" — explicit scope.
- "On my 3B-param run…" — sample caveat.
- "n=1 may not replicate."
- "I have only tested this on 3 teams."
Epistemic-weakness hedge (FLAG): softens without adding information.
- "I think" (when followed by a claim).
- "Perhaps" (standalone).
- "Arguably" — deniability.
- "It could be argued" — auto-deniability.
- "Somewhat" — weakening adverb.
- "Seems" (when no sensing is happening).
- "It seems clear that" — worst-of-both-worlds.
Workflow
For each hedge in the draft:
- [ ] Step 1: Detect hedge markers (modal verbs + phrase list above)
- [ ] Step 2: Classify as precision or weakness
- [ ] Step 3: For weakness, suggest a commit OR a specific hedge (both, as 2 rewrite options)
- [ ] Step 4: For precision, leave alone (note in the "calibrated hedges kept" count)
- [ ] Step 5: Emit the hedge audit with both lists
Step 2: Classifier
A hedge is precision if paired with specific bounds:
- Sample size named (n=1, 3B model, last 12 weeks)
- Scope named ("in three teams I've worked with")
- Specific uncertainty named ("I have not re-derived the gradient")
Otherwise weakness. Default to weakness when unsure — the writer prefers over-flagging here.
Step 3: Rewrite options
For each weakness hedge:
- Option A (commit): remove hedge, take position. "I think batch size matters" → "Batch size matters."
- Option B (specific): name the uncertainty. "I think batch size matters" → "On this 3-run sweep, batch size moved loss by 0.08."
Both options; writer picks.
Worked example
Draft sentences:
- "I think RAG beats fine-tuning for most teams."
- "I do not know whether this holds at 70B — my only test was on a 3B model."
- "Arguably the attention mask is wrong."
- "Perhaps fine-tuning is better when you have very specific stylistic requirements."
Classification:
| # | Hedge | Class | Rewrites |
|---|---|---|---|
| 1 | "I think" | weakness | (a) "RAG beats fine-tuning for most teams." (b) "In the three teams I've worked with, RAG beat fine-tuning." |
| 2 | "I do not know" + scope | precision | Keep as-is. |
| 3 | "Arguably" | weakness | (a) "The attention mask is wrong." (b) "The attention mask looks wrong to me — I have not re-derived the gradient." |
| 4 | "Perhaps" + "very specific" | weakness | (a) "Fine-tuning wins on style." (b) "Fine-tuning wins on style; I have not tested this below 7B." |
Guardrails
- Never flag precision hedges. They are a voice feature.
- Never replace "I do not know" — this is the writer's signature phrase.
- Suggest 2 rewrite options (commit + specific), not 3+.
- Hedge clusters (≥2 weakness hedges within 50 words) get flagged once, collectively — also surfaced to
slop-detectorsignal S8. - Don't flag hedges in quoted text or code fences.
- If the draft is a reflective essay openly admitting uncertainty as its subject, relax the threshold — flag only the most decorative hedges.
Quick reference
- Input: draft.
- Output: hedge audit — weakness hedges with rewrites, precision hedges kept with a count.
- Signal downstream: cluster count goes to
slop-detectorS8.
Signals
- GitHub stars
- 158
- Forks
- 23
- Last commit
- Sep 2026
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hedge-detector- Source
- github.com/lyndonkl/claude