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/claude-code-workflows/recipe-front-designnpx skills add shinpr/claude-code-workflows --skill recipe-front-designgit clone --depth 1 https://github.com/shinpr/claude-code-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/claude-code-workflows/recipe-front-design)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-front-design"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-front-design.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 | $0.00022 | $0.02321 |
| Opus 5 | $0.00011 | $0.01161 |
| Sonnet 5 | $0.00004 | $0.00464 |
| Haiku 4.5 | $0.00002 | $0.00232 |
Grade A, and why
recipe-front-design 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 today.
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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explicit User Instruction: The user explicitly instructs and authorizes every subagent call named in this recipe. Execute each applicable call when its prerequisites are met.
Execute Skill: documentation-criteria before document routing or creation.
Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Execute Skill: subagents-orchestration-guide before invoking agents or resolving findings.
Before the first finding disposition, read references/review-resolution.md from the loaded subagents-orchestration-guide skill.
Outcome and Ownership
Coordinate a Medium/Large frontend design from evidence to an applicable UI Spec and approved Design Doc. The orchestrator owns requirement convergence, Structural Scale, document routing, ADR qualification, evidence selection, and Review Resolution. Named specialists own semantic investigation and artifacts.
The frontend Design Doc always carries the complete implementation design. An ADR batch narrows qualifying technical choices; an applicable UI Spec owns UI structure and behavior that remain to be designed.
Requirements: $ARGUMENTS
Flow
requirement source -> codebase-analyzer -> scope/document routing confirmation [Stop]
|
conditional UI analysis -> UI Spec review [Stop]
|
optional ADR batch/review [Stop]
|
Design Doc -> code-verifier/Resolution -> document-reviewer
|
design-sync -> approval [Stop]
Use Review Resolution for every actionable finding. Wait at each [Stop] for explicit user confirmation.
At each Agent invocation below, build the prompt as a mechanical extraction: copy the named source values into the exact fields, apply only the declared serialization, then invoke immediately.
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.
- today Changed · +1 lines a5c2e927179a
- 5d ago First seen · 159 lines · 22 tokens per session scan A 9cfe7c259fbd
recipe-front-design is a skill published in the GitHub repository shinpr/claude-code-workflows (679 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 2,321 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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