Agent skill

Recipe Front Adjust

by shinpr in shinpr/claude-code-workflows

Adjust an already-implemented UI in-session with verification against the design source

MITAuto-check passedAgent Workflows

Install Recipe Front Adjust

skills CLI
$ npx skills add shinpr/claude-code-workflows --skill recipe-front-adjust -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install shinpr/claude-code-workflows recipe-front-adjust --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/recipe-front-adjust .claude/skills/recipe-front-adjust && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
recipe-front-adjust
GitHub stars
694
Token cost
~2.7k tokens
SKILL.md length
1,250 words
Files
1
Skills in repo
30
Repo updated
First seen
Licence
MIT

At a glance

Adjust an already-implemented UI in-session with verification against the design source

  • Works in 7 steps: External Resource Hearing → Determine the Route and Write Set → Scale Judgment → …
  • Agent Workflows work in your project
  • SKILL.md covers Execution Pattern, Execution Gate, Workflow Overview and Scope Boundaries, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Recipe Front Adjust is an agent skill from shinpr/claude-code-workflows. Adjust an already-implemented UI in-session with verification against the design source

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows. The repository describes itself as: Development workflows for Claude Code that keep broad exploration focused on the outcome you approved. The licence is MIT.

When your agent uses it

  • Agent Workflows work in your project

Example prompts

  • “/recipe-front-adjust”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. External Resource Hearing
  2. Determine the Route and Write Set
  3. Scale Judgment
  4. Adjustment Context
  5. Adjustment + Verification (parent session)
  6. Quality Verification
  7. Commit

What it can do on your machine

Read from SKILL.md and the folder at commit a4ecd62. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Recipe Front Adjust loads about 2.7k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 1,250 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~27
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from shinpr/claude-code-workflows at commit a4ecd62, republished under its MIT licence (© shinpr). 1,250 words, ~2,727 tokens.

Download SKILL.mdSave it as .claude/skills/recipe-front-adjust/SKILL.md (or your agent's skills folder).
name
recipe-front-adjust
description
Adjust an already-implemented UI in-session with verification against the design source
disable-model-invocation
true

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): external-resource hearing via AskUserQuestion, 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

Scope Boundaries

Included in this skill:

  • External resource hearing per the external-resource-context skill
  • Existing-pattern and write-set inspection in the parent session
  • Structural boundary judgment via documentation-criteria
  • Adjustment edits and verification against the design source (run in this session)
  • Quality verification via quality-fixer-frontend
  • Commit the confirmed adjustment outcome

Responsibility Boundary: This skill completes when the confirmed adjustment is committed after its quality cycle and any retained proof limitation receives its final retry. Adjustment work is end-to-end within this recipe; parent session owns edits, verification loops, quality-result routing, and commits.

Escalation Boundary: Escalate to the full frontend design phase when the request crosses a responsibility or approved UI boundary, requires a complete Design Doc, or contains a technical choice that passes documentation-criteria's Choice and Durability filters.

Adjustment request: $ARGUMENTS

Execution Flow

Step 1: External Resource Hearing

Execute Skill: external-resource-context before running the hearing protocol.

Run the hearing protocol only when external evidence can change the current adjustment target or verification result. Otherwise continue with the existing repository/UI Spec evidence and record no external references.

Step 2: Determine the Route and Write Set

Execute Skill: documentation-criteria.

Inspect the named or current UI and the smallest sufficient repository evidence needed to identify the likely write set and preserved visible behavior. Include a generated artifact only when repository tooling shows that a candidate write triggers its generator. When the UI Spec creation condition applies, route to recipe-front-design and stop. Otherwise record the evidence-backed candidate write set for this existing-pattern adjustment.

Step 3: Scale Judgment
  1. Read the candidate write set from Step 2.
  2. Apply Structural Scale to the confirmed outcome and responsibility boundary. Use write-set count as supporting evidence only:
    • 0 files: The adjustment request did not map to any existing file. Escalate to the user with the message "No write target identified from the adjustment request. Please clarify which component(s) should change, or run the full frontend design phase if this is a new feature." Stop this recipe.
    • Direct adjustment: One coherent UI outcome follows existing component, state, interaction, and verification patterns inside one responsibility boundary. Continue directly to adjustment context even when generated or tightly coupled files increase the count.
    • Design required: The change crosses a responsibility or approved UI contract, coordinates independently valuable outcomes, or needs a durable technical choice between credible alternatives. Escalate to the full frontend design phase.
Step 4: Adjustment Context

No work plan. Build a minimal adjustment context for the parent session:

  • Adjustment request (verbatim)
  • Existing UI pattern and preserved visible behavior relevant to the adjustment
  • Evidence-backed affected files list from the candidate write set
  • External resources fetched_summary and access methods that the verification loop will use

Present the adjustment context to the user for review.

  • [STOP]: User confirms the adjustment context covers the work.
Show full SKILL.md (617 more words)Show less
Step 5: Adjustment + Verification (parent session)

Execute Skill: frontend-ai-guide before planning or applying adjustment edits. Execute Skill: typescript-rules before planning or applying adjustment edits. Execute Skill: implementation-approach before planning or applying adjustment edits. Execute Skill: test-implement before adding or changing tests.

Implement the confirmed adjustment outcome across its affected files:

  1. Plan the edit from the confirmed adjustment context and relevant external resource (e.g., design origin's fetched_summary).
  2. Apply the edit using Edit / Write / MultiEdit on the affected files.
  3. Verify against external sources using whichever access method docs/project-context/external-resources.md declares for each axis:
    • Design origin: compare current rendering against the design source via the declared access method (e.g., design-tool MCP, WebFetch from a public URL, file read from a specification path)
    • Visual rendering: capture screenshot or run a smoke check via the declared visual verification method (e.g., browser MCP, E2E test runner CLI invoked via Bash, dev-server URL inspection, Storybook URL)
    • Design system tokens / variants: confirm against the declared design system source (e.g., design-system MCP, package import, Storybook URL, internal documentation path)
  4. Refine and re-verify until the adjustment matches the design source, or matches the user-confirmed adjustment target when no separate design source exists.
  5. When the complete adjustment matches the confirmed target, proceed to Step 6.

When the project-tier file declares no automated verification mechanism for an axis, ask the user to confirm the result manually, or use file-based comparison when a specification file is available.

Step 6: Quality Verification
  • Invoke quality-fixer-frontend using Agent tool
    • subagent_type: "dev-workflows-frontend:quality-fixer-frontend"
    • description: "Quality verification for confirmed adjustment"
    • direct_scope: Copy the confirmed adjustment request and preserved visible behavior from Step 4 unchanged.
    • governing_sources: Pass the existing UI and design source references used for the adjustment unchanged.
    • observable_verification: Pass the confirmed adjustment request from Step 4 and applicable acceptance criteria from the governing sources unchanged.
    • Pass qualityCommand when available (caller first, otherwise current task).
  • Route the quality-fixer-frontend response by status:
    • pass → proceed to Step 7
    • stub_detected → return to Step 5 to complete the confirmed adjustment, then re-invoke quality-fixer-frontend
    • verification_incomplete → retain the complete result for final retry and proceed to Step 7
    • blocked → Apply subagents-orchestration-guide Specialist Result Acceptance using the result's semantic evidence, changed files, and repository state
Step 7: Commit

Before committing, use repository state at the commit boundary as the primary evidence and account for every actual change by mapping it to the confirmed adjustment, preserved pattern, or a necessary dependency, test, or generated artifact. Every required change is ready for the adjustment commit, accidental changes introduced during the adjustment are removed, and existing worktree changes unrelated to the confirmed adjustment remain intact.

Commit the confirmed adjustment after pass or verification_incomplete. For the latter, derive and append one Verification-Limitation: <reason> and Verification-Affected: <affected check or command> trailer pair per retained limitation.

On continuation, reconstruct retained limitations from the verification trailers on commits already completed for this request. After the adjustment is committed, retry each retained verification limitation once with quality-fixer-frontend. When the retry returns pass, remove that limitation from retained state. Commit any resulting fixes through Steps 6→7, and include only a repeated limitation in the completion report.

Completion Criteria

  • External resource hearing executed (project-tier file written or update explicitly skipped)
  • UI Spec applicability and the candidate write set were determined from the requested UI and sufficient repository evidence
  • Structural boundary judgment applied; changes requiring complete design or a qualifying durable decision escalated
  • Adjustment context, including the affected files, was presented and confirmed once
  • The confirmed adjustment outcome is implemented; each declared verification mechanism ran, received manual confirmation where required, or retained its exact proof limitation after final retry
  • The confirmed adjustment completed quality-fixer-frontend before commit; retained proof limitations were retried and reported
  • The confirmed adjustment is committed

Output Example

Frontend adjustment completed.
- External resources: docs/project-context/external-resources.md (updated|unchanged)
- UI evidence: existing pattern [path], external sources [fetched|partial|not_recorded]
- Scale: direct existing-pattern adjustment
- Adjustment commit: [commit hash]
- Quality status: all passed | [remaining proof limitations]

© shinpr, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/recipe-front-adjust of shinpr/claude-code-workflows.

Open the folder on GitHubat commit a4ecd62

Compare with similar skills

Recipe Front Adjust next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Recipe Front Adjust this skillshinpr/claude-code-workflows694—~2.7kAutomated safety check: PassMIT
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Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k10 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k36 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79689 repos~8.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Recipe Front Adjust

What does Recipe Front Adjust do?

Adjust an already-implemented UI in-session with verification against the design source. Recipe Front Adjust is an agent skill from shinpr/claude-code-workflows.

When should I use Recipe Front Adjust?

Recipe Front Adjust fits situations like: agent Workflows work in your project.

How do I install Recipe Front Adjust in Claude Code?

Run `npx skills add shinpr/claude-code-workflows --skill recipe-front-adjust -a claude-code`. Or copy the skill folder (skills/recipe-front-adjust in shinpr/claude-code-workflows) into .claude/skills/recipe-front-adjust in your project. Claude Code loads it when a task matches its description.

How do I install Recipe Front Adjust in Codex?

Run `npx skills add shinpr/claude-code-workflows --skill recipe-front-adjust -a codex`. Or copy the skill folder (skills/recipe-front-adjust in shinpr/claude-code-workflows) into .agents/skills/recipe-front-adjust in your project. Codex loads it when a task matches its description.

Can I use Recipe Front Adjust in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add shinpr/claude-code-workflows --skill recipe-front-adjust -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/recipe-front-adjust, .gemini/skills/recipe-front-adjust, .github/skills/recipe-front-adjust and .opencode/skills/recipe-front-adjust in your project.

What does Recipe Front Adjust need to run?

SKILL.md names no scripts, command-line tools or credentials: Recipe Front Adjust is instructions for the agent only.

Does Recipe Front Adjust access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Recipe Front Adjust safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Recipe Front Adjust use?

Recipe Front Adjust is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Recipe Front Adjust use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Recipe Front Adjust?

Skills that share tags, products or a category with Recipe Front Adjust: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Recipe Front Adjust?

shinpr (a GitHub user) maintains it in shinpr/claude-code-workflows, which has 694 GitHub stars. The repository holds 30 skills in this directory. The repository was last updated on October 1, 2026.

Source: shinpr/claude-code-workflows on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.