engineering-loop

A step-by-step workflow for carrying an approved code change from the current state through implementation, testing, review, and an evidence-based report.

In plain words
What is it for?
Use it for end-to-end repository changes, including reproducing bugs, adding regression tests, implementing fixes, running validation, and reviewing the result.
Why use it?
It keeps feature and bug-fix work grounded in a known starting point and checks that the requested behavior actually works before stopping.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/phelan164/codex-howto/engineering-loop
Any agent
npx skills add Phelan164/codex-howto --skill engineering-loop
Clone the repo
git clone --depth 1 https://github.com/Phelan164/codex-howto

Made for: Claude Code, Codex.

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 733 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00061 $0.00733
Opus 5 $0.00030 $0.00367
Sonnet 5 $0.00012 $0.00147
Haiku 4.5 $0.00006 $0.00073

Measured 2d ago against content hash c67a37ae802c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

engineering-loop 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.

skills/engineering-loop/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Engineering Loop

Own the change from a verified starting point to a reviewed result. Use one agent and this skill alone unless a specialist changes a material decision.

Establish the baseline

  1. Read applicable AGENTS.md files and repository documentation.
  2. Record the requested behavior, constraints, and observable done conditions.
  3. Inspect the branch and working tree; preserve unrelated user-owned changes.
  4. Identify repository-native validation and run the smallest safe baseline that separates pre-existing failures from task regressions.

For a long, cross-stack, or high-risk change, use the templates and failure rules in references/loop-contract.md. When a task is expected to need repeated autonomous iterations or has an explicit retry, time, token, or cost limit, also use references/loop-policy.md. When a defect is intermittent, performance-related, difficult to reproduce, or resists the first evidence-driven pass, use references/hard-debugging.md.

Run the loop

  1. Reproduce the defect, or capture the current behavior for a feature.
  2. Choose the smallest coherent change and the evidence that will prove it.
  3. Add a failing regression test first when practical.
  4. Implement one bounded change and run the narrowest relevant check.
  5. Pause before expanding into an unplanned subsystem, public contract, migration, or external system. Record why the original scope is insufficient and obtain any authority the expansion requires.
  6. Classify failures as product, test, environment, or assumption failures; fix the cause and rerun the affected check.
  7. Run repository-required broader checks after focused checks pass.
  8. Review the complete diff first for task-contract compliance, then for code quality, regressions, security, and maintainability.
  9. Fix consequential findings and rerun checks affected by those fixes.

Keep a compact ledger of confirmed facts, changed files, commands, outcomes, and the next decision. Return concise diagnostics instead of full logs.

Read the full file on GitHub · 73 lines

Files

What ships with it

4 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.

Changes

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.

  1. 2d ago First seen · 73 lines · 61 tokens per session scan A c67a37ae802c

Subscribe to this mod's changes

engineering-loop is a skill published in the GitHub repository Phelan164/codex-howto (3 stars, last pushed 4d ago), licensed MIT. It adds 61 tokens to every session and 733 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.