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-buildnpx skills add shinpr/codex-workflows --skill recipe-buildgit 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-build)<a href="https://agentmods.dev/skills/shinpr/codex-workflows/recipe-build"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/recipe-build.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 | $0.00024 | $0.00867 |
| Opus 5 | $0.00012 | $0.00434 |
| Sonnet 5 | $0.00005 | $0.00173 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
recipe-build 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- recipe-fullstack-build — 86% identical, 42 lines differ
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Required Skills [LOAD BEFORE EXECUTION]
coding-rulestestingai-development-guidesubagents-orchestration-guidellm-friendly-context
Every spawn_agent call uses fork_turns="none" and supplies the exact artifact paths needed by that specialist.
Orchestrator Role
The orchestrator owns plan selection, approval dialogue, task-set computation, routing, commits, and completion reporting. Invoke specialist agents for task decomposition, implementation, test review, quality repair, and final verification. A user-requested plan revision follows Work Plan Approval.
Work plan: $ARGUMENTS
1. Resolve the Work Plan
Apply subagents-orchestration-guide Work Plan Resolution with docs/plans/tasks/{plan-name}-task-*.md as the managed task pattern, excluding basenames that start with integration-tests-.
Report a missing Work Plan as the exact missing prerequisite.
2. Approval Gate
Apply subagents-orchestration-guide Work Plan Approval. When plan-level user approval is absent or ambiguous, ask before agent invocation or task analysis:
Approve this Work Plan as the implementation scope and authorize task decomposition, implementation, quality fixes, and per-task commits?
[path]
Record approval in the plan's existing plan-level status field and proceed to Step 3. A requested change returns through work-planner and document review before this gate.
3. Conditional Environment Preparation
Proceed directly to task generation. Run recipe-prepare-implementation only when the user explicitly requests repository-local setup. If task-local execution later identifies a concrete missing repository capability, resolve it through Orchestrator Escalation Resolution and run the preparation side path when that is the smallest authorized resolution.
4. Compute the Consumed Task Set
The managed set is exactly docs/plans/tasks/{plan-name}-task-*.md implementation task files, excluding basenames that start with integration-tests-. The pending set contains managed files with at least one unchecked task checkbox.
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.
- 4d ago First seen · 71 lines · 24 tokens per session scan A 63a6ae960917
recipe-build is a skill published in the GitHub repository shinpr/codex-workflows (37 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 867 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.
oracle
Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).
chat-complex-documents
Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…