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zen-prompt-measure

Use when optimizing a GitHub Copilot customization artifact with the Zen CLI, running zen optimize/detect/selfcheck, or interpreting a Zen report. Do not use for generic prompt rewriting, hooks, mcp.json, or automatic candidate application.

Quellinformationen

Repository
kimtth/craft-zen-token-optimizer
Letzte Quellaktivität
7. September 2026 um 09:39
Erkannte Sprache von SKILL.md
Englisch
Sterne
1
Forks
0

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
zen-prompt-measure
description
Use when optimizing a GitHub Copilot customization artifact with the Zen CLI, running zen optimize/detect/selfcheck, or interpreting a Zen report. Do not use for generic prompt rewriting, hooks, mcp.json, or automatic candidate application.
# Optimize a Copilot customization artifact Goal: produce a compact semantic rewrite with a usable draft and bounded verification, not a guarantee of identical outputs or universal meaning preservation. Workflow: 1. Run `zen detect PATH` for `AGENTS.md`, `copilot-instructions.md`, `*.instructions.md`, `*.prompt.md`, `*.agent.md`, or `SKILL.md`. 2. Choose the actual target model and a strong rewrite/judge model. 3. Set `--budget` before an unfamiliar run. Semantic mode defaults to a small budget; `--max-metric-calls` is for the opt-in GEPA engine only. 4. Run `zen selfcheck` after optimizer code changes. 5. Run `zen optimize PATH`. 6. Read the report, differences and errors. Get this run's paths from the CLI or manifest, not the path-free report. Review the draft manually; never apply it automatically. For REVIEW_REQUIRED, the CLI asks whether to accept. Yes sets CONFIRMED by user and records the earlier model assessment in the report. Never supply --accept-draft without explicit user authorization; acceptance does not mean the model checks passed or replace the source. The default semantic engine reads the full body and rewrites it, consolidating repetition while preserving actions, constraints, conditions, exceptions, priorities, language, and required public formats. It saves a usable draft before evaluation, then uses direct semantic review, bounded correction, and source-based task comparisons. No supplied labeled dataset is required. GEPA search remains opt-in with `--engine gepa`. Semantic interpretation: - Verification is separate from draft availability. Incomplete evidence, important meaning loss, or insufficient reduction requires review; a saved draft is retained. - Complete but disputed evidence gets one final adjudication inside the shared budget (one schema retry, no provider retry). Model-origin CONFIRMED means the final model resolved every initial flag and found no material regression in either phase; it is not VERIFIED or human approval. Keep the original findings visible. Missing/error evidence, source/draft changes and deterministic token/line gates cannot be overridden. - User-origin CONFIRMED means explicit acceptance of a REVIEW_REQUIRED draft, even with unmet model gates. Keep the original model decision, findings and errors in the report. Source and frozen-file integrity checks still block publication. - Shared baseline defects are not automatically regressions, but cannot excuse lost instructions. Final review reads frozen holdout evidence without changing the draft. - Harmless wording/order/length differences are not regressions. Missing important facts, changed exceptions, or added requirements can be. - Exact answer quotations and unnecessary reasoning/verification narration are not mandatory evaluation conditions. Explicit source requirements cannot be silently removed just because they are verbose. - Validation and holdout remain separate; freeze the candidate before holdout and never use holdout findings as repair feedback. - Malformed model responses have bounded retries; errors never become successful scores. First-generation failure can leave no draft; filesystem failures can prevent a report. Do not promise unconditional generation. - Semantic judgments are model proxies, not proof of equivalence or human understanding. Tokens are local estimates, not billing. Fresh calls do not establish independent samples. - Source hash checks and frozen metadata protect the original. Use current report paths, not a stale candidate from an older run. Semantic mode has no default hard line cap. `--aggressive LINES` or `--aggressive PERCENT%` requests one; it is not evidence of preserved meaning. Optional `--focus task` / `--focus communication` requires exact comment-delimited sections; it does not infer them. GEPA interpretation: `ACCEPT` still requires complete aligned error-free trials, zero candidate critical failures, at most a 5pp drop in independent behavior/reader trial rates, at least one behavior and reader pass per case, non-increasing artifact/median output/reader tokens, and at least 3% combined reduction. Its single-trial validation and small samples can make that tolerance ineffective. GEPA `REJECT`/`INCONCLUSIVE` do not publish candidates. Its default line cap is 50%; `--compare-concision` is GEPA-only measurement, never a selected artifact or GEPA input. See [the runtime guide](../../../docs/documentation.md). Limits: one artifact, response-only single-turn cases, no repository-changing tools, frozen metadata, no hidden reasoning, and no automatic source replacement.
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