implementation-loop

A delegated coding workflow in which Codex, Grok, or Cursor writes the implementation and another review checks the resulting changes. It repeats the cycle when needed and gates delivery on the full test suite.

In plain words
What is it for?
Delegating feature work or bug fixes, reviewing diffs, requesting iterations, running tests, and preparing a pull request when authorized.
Why use it?
It keeps implementation and review independent, reducing the chance that an unverified self-reported success is treated as finished work.

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/olddonkey/olddonkey-skills/implementation-loop
Any agent
npx skills add olddonkey/olddonkey-skills --skill implementation-loop
Clone the repo
git clone --depth 1 https://github.com/olddonkey/olddonkey-skills

Made for: Claude Code, Codex.

Per session 215 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,236 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 $0.00215 $0.06236
Opus 5 $0.00108 $0.03118
Sonnet 5 $0.00043 $0.01247
Haiku 4.5 $0.00021 $0.00624

Measured 3d ago against content hash 10cbe125720b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implementation-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 3d ago.

The scan reads SKILL.md. This mod also ships 29 executable files (backends/codex/dispatch.sh, backends/codex/fixture-driver.sh, backends/codex/selftest.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/implementation-loop/SKILL.md · 225 lines

How it starts

The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementation loop

The implementer writes the code; you own the judgment. The implementer is fast at implementation but it self-reports success, cannot commit, and will hang a machine if pointed at a long test suite. You give it a precise spec, then be the thing that actually verifies and ships. This includes bug fixes: a bug found at review, at the gate, or later is a unit like any other — you diagnose and spec, the implementer implements. Editing code directly "because it's faster" silently inverts the division of labor and costs review its independence.

The loop: decompose → dispatch → review → iterate → gate → publish → next.

Non-negotiables

  1. Review is mandatory and independent. Codex's summary is a claim; the diff is the evidence. Never skip review because it says it's done.
  2. An assumed default never leaves the machine. With no explicit user choice, stop at the working tree — even a local commit can fire hooks/signing. Commit, push, PR, and merge each need the user to have said yes once for this repo, asked at kickoff, not discovered at publish time. Once is once: that authorization is per-repo, persists across sessions until revoked or the work changes character — never re-ask per unit.
  3. Never push straight to the default branch.
  4. The full-suite gate is yours, run by you, with the real exit code. A fix means the code satisfies the test — a weakened assertion, deleted case, or widened tolerance to turn red green is a stop, not a pass.
  5. Don't let the implementer run the full test suite by default — focused subsets only, unless calibration showed the suite is small and fast.

Dials (settle at kickoff, record, stop re-asking)

Dial Options Recommended default
Backend codex / grok / cursor-agent codex; changes are resurfaced (see dials.md)
Stop point worktree / commit / pr / merge recommend pr; assumed default stops at worktree
Dispatch mode implement / read-only implement
Gate policy baseline / strict / skip baseline
On gate red stop / iterate stop
Review depth light / standard / deep standard
Cadence confirm / continuous confirm; continuous fits stop=merge
Fix lane codex / claude-trivial-ok codex

Read the full file on GitHub · 225 lines

Files

What ships with it

48 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. 3d ago First seen · 225 lines · 215 tokens per session scan A 10cbe125720b

Subscribe to this mod's changes

implementation-loop is a skill published in the GitHub repository olddonkey/olddonkey-skills (15 stars, last pushed 15d ago), licensed MIT. It adds 215 tokens to every session and 6,236 once invoked, about $0.0011 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 2026-08-30.

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