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 agentmods add skills/tmj-90/gaffer/refactor-modulenpx skills add tmj-90/gaffer --skill refactor-modulegit clone --depth 1 https://github.com/tmj-90/gafferWhat 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 | $0.00063 | $0.00474 |
| Opus 5 | $0.00032 | $0.00237 |
| Sonnet 5 | $0.00013 | $0.00095 |
| Haiku 4.5 | $0.00006 | $0.00047 |
Grade A, and why
refactor-module 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 yesterday.
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.
What it actually says
Refactor a module
A refactor changes structure, not behaviour. The contract: tests are green before you start and green after, with no scope creep into new features or fixes.
Steps
- Establish the safety net. Run the suite first (
run-tests) and confirm it's green. If the module under refactor is thinly tested, add characterization tests (theadd-unit-testskill) that pin the current behaviour before you touch anything. - Read the lore. Call
search_lore(Memory MCP) for the repo's module boundaries, layering, and naming conventions so the new structure fits the codebase. - Refactor in small, behaviour-preserving steps — extract, rename, move, dedupe — re-running tests after each step. Keep the public interface stable unless the ticket explicitly allows changing it; update call sites if you do.
- Change no behaviour. No new features, no bug fixes, no dependency changes riding along. If you spot a real bug, note it for a separate ticket — don't fix it here.
- Confirm green after. Run the full suite and lint (
run-tests,run-lint) and confirm identical behaviour and no new failures. - Evidence: before/after passing summaries (proving behaviour preserved) and a
diff_summary. Then use therecord-evidenceskill and submit for review.
Rules
- Behaviour-preserving only: tests green before and after, same outcomes.
- No scope creep — no features, fixes, or dependency bumps in a refactor ticket.
- Keep the public interface stable unless the AC says otherwise.
- If you uncover a bug, log it separately; don't fix it inside the refactor.
- Run on a branch (the
create-branchskill), never a protected branch.
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.
- yesterday First seen · 37 lines · 63 tokens per session scan A a0d748c0f5f7
refactor-module is a skill published in the GitHub repository tmj-90/gaffer (2 stars, last pushed 7d ago), licensed Apache-2.0. It adds 63 tokens to every session and 474 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
mobile-developer
Expert knowledge in mobile app development for iOS, Android, and cross-platform solutions.
skill-creator
Create or update AnkaLoop skills. Use when designing, structuring, or packaging skills with scripts, references, and assets. This skill should be used when users want to create a new skill (or update an existing skill) that extends AnkaLoop's capabilities with specialized knowledge, workflows, or tool integrations.
gh-ci-analyzer
使用 gh CLI 分析 GitHub Actions CI 日志，提供结构化的故障诊断和报告.
ai-engineer
Expert knowledge in AI/ML development, model deployment, and MLOps practices.
telegram-sender
Send and edit Telegram messages, and send photos via Bot API. Use when AnkaLoop needs to send text, reply to a specific message, edit an existing message, send an image, or push proactive notifications (cron results, heartbeat alerts, task status). Requires ANKATELEGRAMBOTTOKEN env var.
security-best-practices
Security best practices and vulnerability prevention guidelines.