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/shinpr/codex-workflows/recipe-reviewnpx skills add shinpr/codex-workflows --skill recipe-reviewgit clone --depth 1 https://github.com/shinpr/codex-workflowsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shinpr/codex-workflows/recipe-review)<a href="https://agentmods.dev/skills/shinpr/codex-workflows/recipe-review"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/recipe-review.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.01792 |
| Opus 5 | $0.00013 | $0.00896 |
| Sonnet 5 | $0.00005 | $0.00358 |
| Haiku 4.5 | $0.00003 | $0.00179 |
Grade A, and why
recipe-review 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Required Skills [LOAD BEFORE EXECUTION]
- [LOAD IF NOT ACTIVE]
coding-rules— repository implementation rules - [LOAD IF NOT ACTIVE]
testing— verification and test quality rules - [LOAD IF NOT ACTIVE]
ai-development-guide— review and repair discipline - [LOAD IF NOT ACTIVE]
llm-friendly-context— task file contract - [LOAD IF NOT ACTIVE]
subagents-orchestration-guide— agent coordination and result handling
Spawn rule: every spawn_agent call uses fork_turns="none" so the subagent receives only the task message and explicitly provided context.
Context: Post-implementation quality assurance
Orchestrator Definition
Core Identity: Coordinate review, perform lightweight evidence collection and routing directly, and invoke specialists for semantic review and implementation repair.
Execution Plan: Reuse the active execution plan. When the workflow has multiple dependent actions and no plan exists, create one that tracks them through final verification.
Execution Method
- Implementation review -> Spawn code-reviewer agent
- Security validation -> Spawn security-reviewer agent
- Code-side fix path -> Spawn task-executor agent
- Design-side update path -> Spawn technical-designer in update mode, then document-reviewer, then design-sync when multiple Design Docs exist
- Quality checks -> Spawn quality-fixer agent
- Re-validation -> Spawn code-reviewer / security-reviewer agents
Orchestrator spawns sub-agents and passes structured data between them.
Design Doc (uses most recent if omitted): $ARGUMENTS
Execution Flow
Step 1: Prerequisite Check
Identify the Design Doc in docs/design/. Derive $STEP_1_FILES as the complete change set for the current work from repository history, tracking state, and the working tree. Include committed, staged, unstaged, and untracked paths, and pass the complete set unchanged to both reviewers.
If a single active work plan is explicitly provided or unambiguously resolved for that Design Doc, read its Review Scope line. Otherwise set Work Plan: none and Review Scope: none; do not infer.
What ships with it
1 file 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.
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 Changed dcf0ea59e63c
- 6d ago First seen · 159 lines · 26 tokens per session scan A 21afb2d91fa5
recipe-review is a skill published in the GitHub repository shinpr/codex-workflows (37 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 1,792 once invoked, about $0.0001 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.
Other skills, from other repositories
chrome-cdp
Drive a headless Chrome over the Chrome DevTools Protocol (CDP) for browser QA — navigate, click, fill forms, read the DOM/accessibility tree, screenshot, and assert. Use whenever a task requires loading a web page and interacting with it like a user. Chrome is launched by a bash step (recipe below); this skill…
skill-creator
Create, install, or update skills in the workspace. Use when (1) installing a skill from a URL or remote source, (2) creating a new skill from scratch, (3) updating or restructuring existing skills. Always use this skill for any skill installation or creation task.
metrics-instrumentation
Specification for instrumenting an opik-backend workflow with operational OpenTelemetry metrics — per-stage throughput/latency/error counters and native histograms, dimensioned per-customer (workspace). Use when a pipeline (scoring, ingestion, experiments, jobs) needs per-stage visibility. Covers metric emission only…
peekaboo
Capture and automate macOS UI with the Peekaboo CLI.
new-app
Scaffold a new Atomic Agents project from scratch — create the directory, pyproject.toml, env file, first agent, and a runnable entry point. Use when the user asks to start a new atomic-agents project from scratch, says "scaffold" / "new project" / "start from zero", or runs /atomic-agents:new-app.
oracle
Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).