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/geeksfino/ai-dev-playbook/loop-engineeringnpx skills add Geeksfino/ai-dev-playbook --skill loop-engineeringgit clone --depth 1 https://github.com/Geeksfino/ai-dev-playbookWhat 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 | $0.00204 | $0.02548 |
| Opus 5 | $0.00102 | $0.01274 |
| Sonnet 5 | $0.00041 | $0.00510 |
| Haiku 4.5 | $0.00020 | $0.00255 |
Grade A, and why
loop-engineering 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 2d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loop Engineering Skill
Loop engineering replaces manual prompting with designed systems that prompt agents automatically. This skill scaffolds those systems for a specific project.
Canonical templates: All loop artifacts live in templates/ next to this SKILL.md.
Path A (this skill) and Path B (README direct copy) use the same files. BUILD mode
copies from templates/, applies interview answers at CUSTOMIZE points, and writes
to the project. Never invent structure from memory — read the template files first.
Two modes:
- BUILD — developer wants to create a loop from scratch → Interview, then copy templates
- AUDIT — developer has an existing loop and wants it reviewed → Audit Checklist
Determine which mode applies from context, or ask if unclear.
Mode 1: BUILD — Scaffolding a First Loop
Step 1: Interview the Project (ask these, don't skip)
Before producing any files, collect the following. Ask all at once to save turns.
1. What triggers the work? (CI failures / open issues / commits / manual Slack trigger / all of the above)
2. What does "done" look like for a task? (tests pass / lint clean / PR approved / custom condition)
3. Which toolchain? (Cursor / Claude Code / Codex / other)
4. Where should the loop run? (local machine / GitHub Actions / both)
5. Should agents open PRs automatically, or land everything in an inbox for human review?
6. Do you already have a CLAUDE.md, AGENTS.md, or .cursor/rules? (affects harness + skill paths)
7. What's the budget ceiling per run? (dollar amount or token count — required before shipping)
8. Should deferred follow-ups be `off`, `suggest` (default), or `auto`?
9. Which GitHub repository receives follow-ups? (do not assume it is the checkout repository; for multi-repo ledgers, record `--target-repo` per finding)
10. Which labels and categories require human confirmation? (security, cross-repository, public, or low-confidence are recommended)
If the developer can't answer #2 (the stop condition), stop and resolve it before proceeding. A loop without a verifiable stop condition is the Nodding Loop anti-pattern.
What ships with it
17 files 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.
- references/failure-modes.md 5.3 KB
- references/five-moves.md 5.8 KB
- references/toolchain-map.md 3.7 KB
- templates/dev-loop/checklist.md 1.9 KB
- templates/dev-loop/followups.jsonl 1 B
- templates/dev-loop/inbox/.gitkeep 0 B
- templates/dev-loop/README.md 2.8 KB
- templates/dev-loop/triage.md 1.6 KB
- templates/dev-loop/verify-commands.md 621 B
- templates/evaluator-agent/loop-reviewer.md 3.8 KB
- templates/github-actions/loop-triage.yml 2.5 KB
- templates/loop-triage/loop-triage.md 7.8 KB
- templates/scripts/dev/flush_followups.sh 208 B runs code
- templates/scripts/dev/loop-verify.sh 218 B runs code
- templates/scripts/dev/record_dev_loop_verdict.py 7.8 KB runs code
- templates/scripts/dev/record_followup.py 15 KB runs code
- templates/scripts/dev/test-loop-verify.sh 583 B runs code
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.
- 2d ago First seen · 187 lines · 204 tokens per session scan A 07036d781aec
loop-engineering is a skill published in the GitHub repository Geeksfino/ai-dev-playbook (2 stars, last pushed 24d ago), licensed MIT. It adds 204 tokens to every session and 2,548 once invoked, about $0.0010 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.
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