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Agent skill

Diagnose Fix Loop

by CherryHQ in CherryHQ/cherry-studio-app

Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful…

AGPL-3.0Auto-check passedDevelopment

Install Diagnose Fix Loop

skills CLI
$ npx skills add CherryHQ/cherry-studio-app --skill diagnose-fix-loop -a claude-code

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

GitHub CLI
$ gh skill install CherryHQ/cherry-studio-app diagnose-fix-loop --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/CherryHQ/cherry-studio-app.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/diagnose-fix-loop .claude/skills/diagnose-fix-loop && 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
diagnose-fix-loop
GitHub stars
4k
Token cost
~1.1k tokens
SKILL.md length
560 words
Files
2
Skills in repo
13
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful…

  • Works in 7 steps: State the target outcome. → Run a $diagnose pass. → Make a ranked fix plan. → …
  • Asked to keep debugging
  • SKILL.md covers Loop, Iteration Discipline and Stop Rules
  • Calls npx

What it does

Diagnose Fix Loop is an agent skill from CherryHQ/cherry-studio-app. Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful fix remains or user intervention is required. Requires the diagnose skill; selected installs must also install diagnose. Use when asked to keep debugging, fix and verify, iterate until satisfied, improve after diagnosis, or run a diagnosis/fix/verification loop.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Development. The repository describes itself as: 🍒 This is the mobile version of Cherry Studio. The licence is AGPL-3.0.

When your agent uses it

  • Asked to keep debugging
  • Iterate until satisfied
  • Improve after diagnosis
  • Run a diagnosis/fix/verification loop

Example prompts

  • “/diagnose-fix-loop”

Requirements

  • Node.js

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. State the target outcome.
  2. Run a $diagnose pass.
  3. Make a ranked fix plan.
  4. Implement only the top plan item.
  5. Verify with the original signal.
  6. Re-run $diagnose.
  7. Decide whether to continue.

What it can do on your machine

Read from SKILL.md and the folder at commit 172945d. 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

    Shell commands in SKILL.md call:

    • npx

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

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    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

Diagnose Fix Loop loads about 1.1k tokens when it runs. Until then it costs about 120 tokens; SKILL.md has 560 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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 CherryHQ/cherry-studio-app at commit 172945d, republished under its AGPL-3.0 licence (© CherryHQ). 560 words, ~1,071 tokens.

Download SKILL.mdSave it as .claude/skills/diagnose-fix-loop/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
diagnose-fix-loop
description
Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful fix remains or user intervention is required. Requires the diagnose skill; selected installs must also install diagnose. Use when asked to keep debugging, fix and verify, iterate until satisfied, improve after diagnosis, or run a diagnosis/fix/verification loop.

Diagnose Fix Loop

Use this skill to drive a complete improvement loop, not a single debugging pass.

Before starting, load and follow $diagnose. Treat $diagnose as the evidence engine for each pass; this skill only adds the outer loop that plans, implements, re-runs diagnosis, and decides whether to continue.

This skill owns planning and implementation after $diagnose proves the cause.

Selected installs do not install dependencies automatically. If $diagnose is not installed or available, stop before making changes. Tell the user to install it with:

bash
npx skills add LegendApp/legend-skills --skill diagnose

Then ask them to retry after installation.

Loop

  1. State the target outcome. Anchor the loop to the user's symptom, performance goal, failing test, UX defect, regression, or code quality concern. If the user gave no concrete anchor, create the fastest observable feedback loop first.

  2. Run a $diagnose pass. Complete the evidence loop and record the exact validation signal that will be re-run after the fix. Proceed only when $diagnose reports Proven — 100%. If it reports Incomplete, stop and report the missing evidence. If the user asked for delegation, use it only for bounded evidence collection inside this pass; keep bottleneck ranking, fix selection, code edits, and final interpretation in the main loop.

  3. Make a ranked fix plan. Prefer one smallest credible fix at a time. The plan must include:

    • what evidence supports the change
    • what file or boundary will change
    • what validation should improve
    • what would make the plan wrong

  4. Implement only the top plan item. Keep the edit scoped to the proven fault line. Avoid stacking speculative cleanup, broad refactors, or adjacent improvements unless the diagnosis showed they are part of the same fault.

  5. Verify with the original signal. Re-run the reproduction path or measurement from step 2, then focused regression coverage, then broader checks when the touched surface warrants them.

  6. Re-run $diagnose. Diagnose the new state from evidence, not from the intent of the change. Look for:

    • the original symptom still failing
    • a nearby remaining fault
    • a regression introduced by the fix
    • a stronger next bottleneck revealed by the first fix
    • missing coverage at the real seam

  7. Decide whether to continue. Continue when evidence identifies a credible next fix and the next action is safe to take. Each new iteration should have a sharper target than the previous one.

Show full SKILL.md (177 more words)Show less

Iteration Discipline

Keep a short running log while working:

  • iteration number
  • current evidence
  • chosen fix
  • validation result
  • next remaining issue or stop reason

If an experiment fails, revert it unless it is independently useful and intentionally kept. Do not count a failed experiment as progress unless it narrowed the diagnosis.

If two iterations produce no measurable improvement and no sharper evidence, pause implementation and re-diagnose the feedback loop itself before making more edits.

Stop Rules

Stop only when one of these is true:

  • $diagnose cannot build or run a credible feedback loop with available code, tools, or artifacts
  • the next action requires user input, inaccessible external state, credentials, production access, or a destructive operation
  • the user requested read-only diagnosis and the next useful step would edit files
  • validation is clean and a fresh $diagnose pass finds no remaining credible fault to fix
  • remaining improvements are speculative, cosmetic, or outside the user's target outcome

When stopping, report the final state, the validation evidence, remaining known risk, and the smallest user action or artifact needed if work is blocked.

© CherryHQ, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .agents/skills/diagnose-fix-loop of CherryHQ/cherry-studio-app.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 172945d

Compare with similar skills

Diagnose Fix Loop 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.

Diagnose Fix Loop compared with similar skills
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Diagnose Fix Loop this skillCherryHQ/cherry-studio-app4k—~1.1kAutomated safety check: PassAGPL-3.0
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT

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Categories

Questions about Diagnose Fix Loop

What does Diagnose Fix Loop do?

Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful…. Diagnose Fix Loop is an agent skill from CherryHQ/cherry-studio-app. Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful fix remains or user intervention is required.

When should I use Diagnose Fix Loop?

Diagnose Fix Loop fits situations like: asked to keep debugging; iterate until satisfied; improve after diagnosis; run a diagnosis/fix/verification loop.

How do I install Diagnose Fix Loop in Claude Code?

Run `npx skills add CherryHQ/cherry-studio-app --skill diagnose-fix-loop -a claude-code`. Or copy the skill folder (.agents/skills/diagnose-fix-loop in CherryHQ/cherry-studio-app) into .claude/skills/diagnose-fix-loop in your project. Claude Code loads it when a task matches its description.

How do I install Diagnose Fix Loop in Codex?

Run `npx skills add CherryHQ/cherry-studio-app --skill diagnose-fix-loop -a codex`. Or copy the skill folder (.agents/skills/diagnose-fix-loop in CherryHQ/cherry-studio-app) into .agents/skills/diagnose-fix-loop in your project. Codex loads it when a task matches its description.

Can I use Diagnose Fix Loop 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 CherryHQ/cherry-studio-app --skill diagnose-fix-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/diagnose-fix-loop, .gemini/skills/diagnose-fix-loop, .github/skills/diagnose-fix-loop and .opencode/skills/diagnose-fix-loop in your project.

What does Diagnose Fix Loop need to run?

Going by SKILL.md and its folder, Diagnose Fix Loop needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Diagnose Fix Loop access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Diagnose Fix Loop 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 Diagnose Fix Loop use?

Diagnose Fix Loop is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Diagnose Fix Loop use?

About 1.1k tokens (SKILL.md is roughly 4.3k 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 Diagnose Fix Loop?

Skills that share tags, products or a category with Diagnose Fix Loop: Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Diagnose Fix Loop?

CherryHQ (a GitHub organization) maintains it in CherryHQ/cherry-studio-app, which has 3,972 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 3, 2026.

Source: CherryHQ/cherry-studio-app on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.