Agent skill

Agent Design Review

by dcramer in dcramer/peated

Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Agent Design Review

skills CLI
$ npx skills add dcramer/peated --skill agent-design-review -a claude-code

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

GitHub CLI
$ gh skill install dcramer/peated agent-design-review --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/dcramer/peated.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agent-design-review .claude/skills/agent-design-review && 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
agent-design-review
GitHub stars
102
Token cost
~1.4k tokens
SKILL.md length
652 words
Files
4 (incl. references)
Skills in repo
7
Repo updated
First seen
Licence
Apache-2.0

At a glance

Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details.

  • Works in 5 steps: State The Job → Map What Runs → Find The Layer That Failed → …
  • Asked to design an agent
  • SKILL.md covers 1. State The Job, 2. Map What Runs, 3. Find The Layer That Failed and 4. Check Who Decides What, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Agent Design Review is an agent skill from dcramer/peated. Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details. Use when asked to "design an agent", "review this agent", "improve a prompt", "fix tool calling", "add structured output", "reduce wrong matches", "decide if this needs another agent", or "add model checks".

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/peated-classifiers.md`, `references/prompts.md` and `references/tools-and-schemas.md`).

It sits in AI & LLM Engineering, covering Structured output and tool calling and Design review and critique. The licence is Apache-2.0.

When your agent uses it

  • Asked to design an agent
  • Review this agent
  • Improve a prompt
  • Fix tool calling

Example prompts

  • “design an agent”
  • “review this agent”
  • “improve a prompt”
  • “/agent-design-review”

Workflow steps

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

  1. State The Job
  2. Map What Runs
  3. Find The Layer That Failed
  4. Check Who Decides What
  5. Prove It

What it can do on your machine

Read from SKILL.md and the folder at commit aee6890. 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

Agent Design Review loads about 1.4k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 652 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.2k

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 dcramer/peated at commit aee6890, republished under its Apache-2.0 licence (© dcramer). 652 words, ~1,434 tokens.

Download SKILL.mdSave it as .claude/skills/agent-design-review/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
agent-design-review
description
Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details. Use when asked to "design an agent", "review this agent", "improve a prompt", "fix tool calling", "add structured output", "reduce wrong matches", "decide if this needs another agent", or "add model checks".

Agent Design Review

Read docs/policies/agent-design.md first. If this skill disagrees with it, the policy wins; fix this skill.

Load only what applies:

NeedRead
Work on the Bottle or Entity classifierreferences/peated-classifiers.md
Write or change a promptreferences/prompts.md
Write or change a tool, tool input, or output schemareferences/tools-and-schemas.md
Add, run, or read model checksdocs/development/model-checks.md
Decide what may go into prompts, tool results, or logsdocs/policies/sensitive-data.md
Retries, fallbacks, and failuresdocs/policies/error-handling.md

Match the effort to the request. A tool description fix does not need a full review.

1. State The Job

Write down, briefly:

  • what the model decides, and what it returns
  • which mistakes are costly (a wrong match usually costs more than no_match)
  • what it may change, and who approves that change

2. Map What Runs

Read the code, not just the prompt. List:

  • the input and who builds it
  • what code decides before the model runs (exact lookups, known IDs, ignored input)
  • how candidates and evidence are found
  • the instructions, tools, and output schema
  • run limits (maxTurns, web search budgets, parallelToolCalls)
  • what code checks after the model returns
  • how auto versus review is decided, and what is saved
  • which model checks cover it

3. Find The Layer That Failed

Use the layers from model-checks.md:

LayerSign
Input contextThe model never saw a fact it needed
RetrievalThe right Bottle or Entity was not in the candidates
Tool executionA tool errored, returned too much, or returned prose the model misread
Model judgmentGood candidates and evidence, wrong choice
Code reviewCode after the model rejected, changed, or passed the wrong thing
IntegrationThe decision was right but the saved state is wrong
ExpectationThe test case expected the wrong answer

Fix that layer first. Change the prompt only when the model had what it needed and still chose wrong.

Show full SKILL.md (349 more words)Show less

4. Check Who Decides What

  • The model decides meaning. Identity, intent, source quality, and whether two things are the same. Regexes, keyword lists, fuzzy-name scores, and search rank may find candidates. They must not make the final call or overrule the model.
  • Code enforces rules. Syntax, known IDs, schema shape, permissions, saved state, safe repeats, and direct conflicts between filled-in fields.
  • Code after the model may reject or send to review. It must not swap one decision for another.
  • No confidence numbers. Code sets auto or review from the action, evidence, and open risks.
  • The model proposes; the server decides. Approval and writes that cannot be undone stay in code, apart from the model's proposal.
  • No fallback by default. A backup model, provider, or tool is new behavior. Report the missing service unless a fallback is defined and tested.
  • Every run has limits. Turns, tool calls, web searches, and retries.
  • Input is data. Listing text, web pages, and tool results are never instructions.
  • One agent before several. Add another only for a different contract, different tools or permissions, or a measured gain.

5. Prove It

Every behavior change needs a model check that fails before and passes after. Follow model-checks.md. Start a production miss from its saved run, not Sentry. Fixed rules get ordinary tests.

Output

Include only the parts that apply, and say what you skipped.

For a review or a failure:

  1. What runs today, briefly
  2. The layer that failed
  3. Findings, worst first: layer, evidence (file and line, saved run, or test case), effect, and smallest fix
  4. The model checks that will show the fix worked

For a new design:

  1. The job
  2. What runs, and what code versus the model decides
  3. Prompt outline, tools, and output schema
  4. Limits, approvals, and what is saved
  5. Model checks

Weak finding: "Improve the prompt and add an example."

Strong finding: "Retrieval. The saved run shows the correct Bottle was never in the candidates because the search dropped the age. Pass age to search_bottles and add a model check for an age-only near match."

© dcramer, Apache-2.0. 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 3 other files (references) in skills/agent-design-review of dcramer/peated.

  • SKILL.md
  • references/peated-classifiers.md
  • references/prompts.md
  • references/tools-and-schemas.md

Open the folder on GitHubat commit aee6890

Compare with similar skills

Agent Design Review 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.

Agent Design Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Design Review this skilldcramer/peated102—~1.4kAutomated safety check: PassApache-2.0
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Ax Audiodosco/aithy107—~2.5kAutomated safety check: PassApache-2.0
Planning With Filesjarrodwatts/claude-code-config1.1k5 repos~967Automated safety check: PassNone
Gemini API Devgoogle-gemini/gemini-skills4.3k—~5.1kAutomated safety check: PassApache-2.0
AI SDK Developmenttrypostit/trypost6782 repos~3.5kAutomated safety check: PassMIT

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Questions about Agent Design Review

What does Agent Design Review do?

Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details. Agent Design Review is an agent skill from dcramer/peated. Designs, reviews, and debugs Peated's model-driven code, such as the Bottle and Entity classifiers, extractors, price matching, and generated details.

When should I use Agent Design Review?

Agent Design Review fits situations like: asked to design an agent; review this agent; improve a prompt; fix tool calling.

How do I install Agent Design Review in Claude Code?

Run `npx skills add dcramer/peated --skill agent-design-review -a claude-code`. Or copy the skill folder (skills/agent-design-review in dcramer/peated) into .claude/skills/agent-design-review in your project. Claude Code loads it when a task matches its description.

How do I install Agent Design Review in Codex?

Run `npx skills add dcramer/peated --skill agent-design-review -a codex`. Or copy the skill folder (skills/agent-design-review in dcramer/peated) into .agents/skills/agent-design-review in your project. Codex loads it when a task matches its description.

Can I use Agent Design Review 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 dcramer/peated --skill agent-design-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-design-review, .gemini/skills/agent-design-review, .github/skills/agent-design-review and .opencode/skills/agent-design-review in your project.

What does Agent Design Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Agent Design Review is instructions for the agent only.

Does Agent Design Review 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 Agent Design Review 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 Agent Design Review use?

Agent Design Review is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Design Review use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Agent Design Review?

Skills that share tags, products or a category with Agent Design Review: Xsai (moeru-ai/airi, 50k stars), Ax Audio (dosco/aithy, 107 stars), Planning With Files (jarrodwatts/claude-code-config, 1.1k stars) and Gemini API Dev (google-gemini/gemini-skills, 4.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Design Review?

dcramer (a GitHub user) maintains it in dcramer/peated, which has 102 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 2, 2026.

Source: dcramer/peated on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.