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Discovers and analyzes scripts in the repository, scoring them for utility and integration. Produces SYNC_REPORT.md with recommendations for integration, archival, or deletion of each script.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Experiment orchestration framework with traffic allocation, statistical analysis, and early stopping detection. Use to test routing changes, model upgrades, and role assignments with Welch's t-test significance testing.
DEPRECATED — This skill is no longer maintained. Prometheus and Grafana infrastructure was never implemented. Use local JSON metrics analysis instead.
Scaffolds new SPEC-compliant agentic-engineers agents with a single call. Generates SKILL.md frontmatter, test scaffolds (TDD RED-phase), __init__.py, scripts/ layout, and DELEGATE/HANDBACK protocol templates. Use when creating any new automation agent, task handler, or operational tool. Validates role, model, effort, naming, and dependency graphs (circular dep detection) before writing files. Supports dry-run mode for planning without side effects.
Routine maintenance for Codex sessions: monitor queue state, close completed sub-agents, resume or escalate active work, and keep agent capacity available.
Automated cross-validation of protocol queue integrity. Scans all DELEGATEs/HANDBACKs, validates schema compliance, detects cycles, checks rate limits, generates compliance report. Enables self-referential protocol improvements.
Consolidates provider-specific AI costs into unified metrics across Anthropic, OpenAI, Google Gemini, GitHub Copilot, and Ollama. Enables apples-to-apples cost comparison and savings analysis.
| name | file-sync |
| description | Discovers and analyzes scripts in the repository, scoring them for utility and integration. Produces SYNC_REPORT.md with recommendations for integration, archival, or deletion of each script. |
| license | Proprietary |
| compatibility | agentic-engineers framework v5.10+ |
| metadata | {"author":"agentic-engineers","version":"1.0","category":"hygiene","role":"senior-engineer","model":"haiku-4-5","effort":"medium","trigger":"on-demand | pre-cleanup","tdd_phase":"GREEN"} |
file-sync analyzes all scripts in the repository and generates a
SYNC_REPORT.md that categorizes each script by value and integration status.
| Category | Meaning |
|---|---|
| HIGH_VALUE + unintegrated | Should be integrated (Makefile, CI, docs, imports) |
| HIGH_VALUE + integrated | Well-maintained — leave alone |
| MEDIUM + unintegrated | Optional — consider integrating or documenting |
| DEAD | Debug/temp code — clean up |
| Signal | Weight |
|---|---|
| Quality (docstring, type hints, error handling) | ~3 pts |
| Maturity (naming, LOC, no dev-markers) | ~3 pts |
| Relevance (CONTRIBUTING.md mention, core domain) | ~2.5 pts |
| Dependencies (minimal deps preferred) | ~1.5 pts |
Searches for references to each script in:
Makefile targets.github/workflows/ CI filesimport statements*.md documentationpython scripts/file_sync.py [--root <dir>] [--output <path>]
Output: SYNC_REPORT.md in the repository root.
This skill participates in the framework's continuous improvement cycle (see skill-improvement-feedback).
When you use file-sync during a task, include a skill_feedback entry in your HANDBACK to help improve it over time:
skill_feedback:
- skill_name: file-sync
effectiveness_score: 0.85 # required: 0.0–1.0
clarity_score: 0.90 # optional
coverage_gaps:
- "Specific scenario the skill did not address"
improvement_suggestions:
- "Concrete change that would have helped"
usage_context: "One sentence on how you used this skill"
Positive feedback is as valuable as critical feedback. Three or more feedback items for this skill automatically trigger an improvement task.