Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add chrono-meta/forge-harness --skill dialogue-harvestgit clone --depth 1 https://github.com/chrono-meta/forge-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chrono-meta/forge-harness/dialogue-harvest)<a href="https://agentmods.dev/skills/chrono-meta/forge-harness/dialogue-harvest"><img src="https://agentmods.dev/badge/skills/chrono-meta/forge-harness/dialogue-harvest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chrono-meta/forge-harness/dialogue-harvest"><img src="https://agentmods.dev/badge/skills/chrono-meta/forge-harness/dialogue-harvest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 6 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00165 | $0.03416 |
| Opus 5 | $0.00082 | $0.01708 |
| Sonnet 5 | $0.00033 | $0.00683 |
| Haiku 4.5 | $0.00016 | $0.00342 |
Grade A, and why
dialogue-harvest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Triggers
- "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" / "이 대화에서 내 몫이 뭐였지"
- "turn this dialogue into propositions" / "이 대담 명제로 정리해줘"
/dialogue-harvest {path or pasted log}
Boundary: wrapping up the current session → harvest-loop; this skill mines an
external/pasted dialogue corpus.
Step 0. Input Acquisition
- Path provided → Read the file.
- Pasted log → use as-is.
- No speaker structure detectable (no turn markers, no names, no quoting pattern) → stop and ask:
Speaker separation is the first operation and it needs turn boundaries. Who said what? (Provide turn markers, or confirm the text is single-author — single-author texts skip Steps 1–2 and go straight to proposition-ization.)
Single-author path: skip Steps 1–2, Step 4 stamps every proposition independent (no
counterpart exists), and the Step 6 counterpart sections read n/a.
Step 1. Speaker Separation (mechanical when markers exist)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 224 lines · 165 tokens per session scan A 1964df983d85
dialogue-harvest is a skill published in the GitHub repository chrono-meta/forge-harness (14 stars, last pushed yesterday), licensed MIT. It adds 165 tokens to every session and 3,416 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
taiyi-integration
A project workflow skill for closing a TaiyiForge change and recording it in a CHANGELOG.md file. It checks review results, tests, and the state of the working tree before archiving the change.
taiyi-requirement
A requirements-analysis process that turns a proposed change into a REQUIREMENT.md document. It records user needs, acceptance checks, terminology, triggers, and dependencies, with different levels of detail for different project sizes.
taiyi-change
A TaiyiForge workflow stage for writing a change proposal in CHANGE.md, with checks for scope, risks, success criteria, and related project documents.
taiyi-test
A project workflow skill for verifying an implementation and producing a TEST.md record. TDD means writing a failing test, implementing the change, and then making the test pass; this skill checks that process and other regression cases.
taiyi-ui-design
A design-planning guide for describing how an application's user interface should look and behave. It produces a UI-DESIGN.md document covering layouts, components, interactions, accessibility, and error states.
taiyi-compress
A workflow tool for shrinking large coding-agent conversations and work files into shorter context notes. It can also coordinate separate agents for parallel development and create handoff notes for continuing work in a new session.