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 skills add shinpr/codex-workflows --skill recipe-fullstack-implementgit 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-fullstack-implement)<a href="https://agentmods.dev/skills/shinpr/codex-workflows/recipe-fullstack-implement"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/recipe-fullstack-implement/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shinpr/codex-workflows/recipe-fullstack-implement"><img src="https://agentmods.dev/badge/skills/shinpr/codex-workflows/recipe-fullstack-implement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00745 |
| Opus 5.5 | $0.00008 | $0.00298 |
| Sonnet 5.5 | $0.00004 | $0.00149 |
| Haiku 4.5 | $0.00002 | $0.00075 |
Grade A, and why
recipe-fullstack-implement 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 16d 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 — 44 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]
subagents-orchestration-guide— Fullstack (Monorepo) Flow, approvals, and autonomous execution - [LOAD IF NOT ACTIVE]
documentation-criteria— scale-selected document path - [LOAD IF NOT ACTIVE]
requirement-convergence— outcome, exclusions, and rough-cost challenge - [LOAD IF NOT ACTIVE]
llm-friendly-context— cross-agent handoffs and Small task carrier
Invocation rule: Start each named agent with spawn_agent and fork_turns="none". When invoking the same named agent again within this flow, use followup_task on its existing instance with the inputs specified for the current invocation. Supply only the exact artifacts needed by that specialist.
Requirements or continuation instruction: $ARGUMENTS
Entry
- New or scope-changing requirements: apply the subagents-orchestration-guide Requirement Evidence Handoff and invoke requirement-analyzer for compact scope/cost evidence; user selections establish requirements and exclusions, while the orchestrator judges readiness and determines scale and layer routing.
- Existing PRD, UI Spec, Design Docs, Work Plan, or tasks: resume at the next incomplete Fullstack (Monorepo) Flow phase. Restart requirement analysis when the approved outcome, requirement, or exclusion changes.
- Quality failure during an existing implementation: resume its task cycle and Orchestrator Escalation Resolution.
For a requirements stop, read requirement-convergence's references/scope-confirmation.md and render that output from the retained user record and analyzer evidence. Render each unanswered product, UX, or operational decision under User decisions as an unresolved question followed by its answer-dependent effects. Only an explicit user selection moves it into Confirmed scope. Record Structural Scale and workflow routing under Workflow.
Resolve the entry from supplied artifacts and repository state. Ask only when different interpretations require a change to user-required outcomes, explicit constraints, or execution authority.
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.
- 16d ago Changed ea27e479d0e3
- 1mo ago Changed · +2 lines b47a1b291827
- 1mo ago Changed e08088791fe4
- 1mo ago First seen · 42 lines · 21 tokens per session scan A 94665249b83c
recipe-fullstack-implement is a skill published in the GitHub repository shinpr/codex-workflows (39 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 745 once invoked, about $0.0001 per session on Opus 5.5. 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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