Individual skill
dialogue-harvest
Mines improvement insights from long-form AI dialogue logs and long texts — an external or pasted corpus, not the current session (current-session wrap-up belongs to harvest-loop). First operation is sycophancy removal — separates speakers, strips the counterpart's agreement/restatement spans, converts the user's own utterances into falsifiable propositions, and labels each proposition induced (frame first introduced by the counterpart) or independent (originated with the user). Ships a drop counter so removed material is visible, never silently lost. Triggered by "mine insights from this chat log", "이 대화록에서 통찰 캐줘", "strip the agreement and show me what's actually mine", "동조 걷어내고 알맹이만", "what did I actually contribute in this thread".
plugins/fh-meta/skills/dialogue-harvest/SKILL.md
Source commit 86a7a68a70a3812c05713f64081ca42a5bfddaa8
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- Matches the observed repository HEAD
- Yes
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- Observed behavior
- Not checked yet
- Last checked
- Nov 6, 2026
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- Repository stars (not skill ratings)
- 31
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- knowledge-management Repository topic
- codex Repository topic
- harness Repository topic
- claude-code Repository topic
- multi-agent Repository topic
- meta-harness Repository topic
- agent-governance Repository topic
- self-evolving Repository topic
- agentic-coding Repository topic
- loop-engineering Repository topic
- engineering Derived category
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# dialogue-harvest
Extracts the load-bearing propositions from a long AI-human dialogue (or long text) after
removing the counterpart's sycophancy. Fills the gap between FH's loading assets
(corpus-grounding-expander, video-ingest) and its mining assets (frontier-digest = feed items,
field-harvest = git history, harvest-loop = session records): none of those mines an *argument-shaped*
corpus, and a naive summarizer run on an AI dialogue returns "the user made several excellent
points" — worthless, because most of the volume is agreement.
**Why the first operation is sycophancy removal**: AI dialogue logs are dominated by agreement and
restatement. Without stripping them first, extraction inflates the user's contribution; without
provenance labeling (Step 4), "my insight" and "a frame the counterpart planted" are
indistinguishable — which is exactly the failure this skill exists to prevent.
