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/claude-code-workflows --skill recipe-front-adjustgit 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-adjust)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-front-adjust"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-front-adjust/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/claude-code-workflows/recipe-front-adjust"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-front-adjust.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 | $0.00018 | $0.01976 |
| Opus 5.5 | $0.00007 | $0.00790 |
| Sonnet 5.5 | $0.00004 | $0.00395 |
| Haiku 4.5 | $0.00002 | $0.00198 |
Grade A, and why
recipe-front-adjust 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 8d 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 — 150 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: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Context: UI adjustment on already-implemented features. The verification loop (edit → check against the design source → refine) runs in the parent session.
Execution Pattern
Core Identity: "I am a guided executor. I run the adjustment and the verification loop myself; subagents handle one-shot tasks."
Execution Protocol:
- Delegate to subagents (one-shot calls): quality-fixer-frontend.
- Run in the parent session (multi-step loops and user dialogs): conditional external-evidence resolution, with AskUserQuestion for missing decision-relevant inputs, write-set inspection, scale judgment, adjustment-context approval, adjustment edits, verification against the design source, iteration until acceptance.
- Stop at every
[Stop: ...]marker before proceeding.
Execution Gate
Complete Steps 1-7 in order for the confirmed adjustment outcome. Advance only through the current step's stated evidence, quality result, or user stop; skip work only when its stated condition is false. Report completion after every applicable Completion Criterion and retained-limitation retry is satisfied.
Workflow Overview
Adjustment request → conditional external resource evidence
↓
existing-pattern and write-set inspection
↓
structural boundary judgment on candidate write set
↓
local existing-pattern adjustment → [Stop]
↓
adjustment + verification (parent session)
↓
quality-fixer-frontend (subagent: typecheck/lint/test)
↓
commit
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.
- 8d ago Changed · -3 lines 0a15e3dd0b9e
- 14d ago Changed 718c35964cd7
- 1mo ago Changed 3f154f48638e
- 1mo ago Changed · +1 lines 993b39ede5ea
- 1mo ago First seen · 152 lines · 18 tokens per session scan A d33bdf764c0d
recipe-front-adjust is a skill published in the GitHub repository shinpr/claude-code-workflows (704 stars, last pushed 5d ago), licensed MIT. It adds 18 tokens to every session and 1,976 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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