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-front-buildnpx skills add shinpr/codex-workflows --skill recipe-front-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-front-build)<a href="https://agentmods.dev/skills/shinpr/codex-workflows/recipe-front-build"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/recipe-front-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 5.1 | $0.00025 | $0.00808 |
| Opus 5 | $0.00013 | $0.00404 |
| Sonnet 5 | $0.00005 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
recipe-front-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 5d 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 — 61 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 exact artifact paths.
Orchestrator Role
The orchestrator owns plan selection, approval dialogue, task-set computation, routing, commits, and completion reporting. Invoke specialist agents for task decomposition, frontend 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}-frontend-task-*.md as the managed task pattern, excluding basenames that start with integration-tests-. Report a missing plan as the exact 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, frontend 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. Task Set and Execution Plan
The managed set is exactly docs/plans/tasks/{plan-name}-frontend-task-*.md implementation task files whose basename does not start with integration-tests-. The pending set contains managed files with at least one unchecked task checkbox. When the managed set is empty, invoke task-decomposer with the exact approved Work Plan path, verify the generated task files, and recompute both sets. Batch approval authorizes decomposition. When the managed set exists and the pending set is empty, proceed to final verification.
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.
- 5d ago First seen · 61 lines · 25 tokens per session scan A d97cca318079
recipe-front-build is a skill published in the GitHub repository shinpr/codex-workflows (37 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 808 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.
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