recipe-front-adjust

recipe-front-adjust is a skill for Claude Code from shinpr/claude-code-workflows. It costs 18 tokens per session (1,976 once invoked), scanned A, original, MIT.

A guided workflow for changing an existing user interface while checking each change against its original design source.

In plain words
What is it for?
Use it to adjust already-built screens, inspect the affected files, make approved visual edits, and refine them until they match the design source.
Why use it?
It reduces the risk of making visual changes that drift from the approved design. It also separates one-time helper tasks from the repeated edit-and-check process.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: mentions subagents; names the AskUserQuestion tool.

Part of the dev-workflows-frontend plugin — 9 skills shipped together

Good fit Use it to adjust already-built screens, inspect the affected files, make approved visual edits, and refine them until they match the design source.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shinpr/claude-code-workflows/recipe-front-adjust
Install

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.

Any agent
npx skills add shinpr/claude-code-workflows --skill recipe-front-adjust
Clone the repo
git clone --depth 1 https://github.com/shinpr/claude-code-workflows

Made for: Claude Code.

Or install dev-workflows-frontend, the plugin that ships this one along with the rest of its 9 skills.

Wrote 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.

agentmods badge for recipe-front-adjust

README.md
[![agentmods](https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-front-adjust/github.svg)](https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-front-adjust)
Your own site
<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.

agentmods 80×15 button for recipe-front-adjust

Your own site · 80×15
<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>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,976 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 8d ago against content hash 0a15e3dd0b9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

dev-workflows-frontend/skills/recipe-front-adjust/SKILL.md · 150 lines

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:

  1. Delegate to subagents (one-shot calls): quality-fixer-frontend.
  2. 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.
  3. 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

Read the full file on GitHub · 150 lines

Changes

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.

  1. 8d ago Changed · -3 lines 0a15e3dd0b9e
  2. 14d ago Changed 718c35964cd7
  3. 1mo ago Changed 3f154f48638e
  4. 1mo ago Changed · +1 lines 993b39ede5ea
  5. 1mo ago First seen · 152 lines · 18 tokens per session scan A d33bdf764c0d

Subscribe to this mod's changes

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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