Hedge Detector

SkillAI & models

Classifies 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.

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:

  1. "I think RAG beats fine-tuning for most teams."
  2. "I do not know whether this holds at 70B — my only test was on a 3B model."
  3. "Arguably the attention mask is wrong."
  4. "Perhaps fine-tuning is better when you have very specific stylistic requirements."

Classification:

#HedgeClassRewrites
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" + scopeprecisionKeep 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

  1. Never flag precision hedges. They are a voice feature.
  2. Never replace "I do not know" — this is the writer's signature phrase.
  3. Suggest 2 rewrite options (commit + specific), not 3+.
  4. Hedge clusters (≥2 weakness hedges within 50 words) get flagged once, collectively — also surfaced to slop-detector signal S8.
  5. Don't flag hedges in quoted text or code fences.
  6. 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-detector S8.

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
hedge-detector
Source
github.com/lyndonkl/claude