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Agent skill

Skill Review Response

by nyldn in nyldn/claude-octopus

A skill your agent uses when a reviewer, CI bot, or another AI leaves feedback to address

MITAuto-check passed

Install Skill Review Response

skills CLI
$ npx skills add nyldn/claude-octopus --skill skill-review-response -a claude-code

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

GitHub CLI
$ gh skill install nyldn/claude-octopus skill-review-response --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/nyldn/claude-octopus.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skill-review-response .claude/skills/skill-review-response && 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
skill-review-response
GitHub stars
4.2k
Used in
1 other repo
Token cost
~1.1k tokens
SKILL.md length
489 words
Files
2
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when a reviewer, CI bot, or another AI leaves feedback to address

  • Works in 3 steps: What you checked → Why the suggestion doesn't apply → Evidence (line numbers, call sites, tests)
  • Another AI leaves feedback to address
  • SKILL.md covers Core Principle, The Response Pattern, Forbidden Responses and Evaluation Checklist, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Skill Review Response is an agent skill from nyldn/claude-octopus. Use when a reviewer, CI bot, or another AI leaves feedback to address

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`).

The repository describes itself as: Run multiple AI models against the same research, design, or coding task. Surface disagreements before you ship. The licence is MIT.

When your agent uses it

  • Another AI leaves feedback to address

Example prompts

  • “/skill-review-response”

Workflow steps

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

  1. What you checked
  2. Why the suggestion doesn't apply
  3. Evidence (line numbers, call sites, tests)

What it can do on your machine

Read from SKILL.md and the folder at commit b34780d. 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 (its code samples are markdown).

    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

Skill Review Response loads about 1.1k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 489 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
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 nyldn/claude-octopus at commit b34780d, republished under its MIT licence (© nyldn). 489 words, ~1,093 tokens.

Download SKILL.mdSave it as .claude/skills/skill-review-response/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
skill-review-response
description
Use when a reviewer, CI bot, or another AI leaves feedback to address
disable-model-invocation
true

Host: Codex CLI — This skill was designed for Claude Code and adapted for Codex. Cross-reference commands use installed skill names in Codex rather than /octo:* slash commands. Use the active Codex shell and subagent tools. Do not claim a provider, model, or host subagent is available until the current session exposes it. For host tool equivalents, see skills/blocks/codex-host-adapter.md.

Receiving Code Review

Core Principle

Code review requires technical evaluation, not performative agreement.

Never blindly implement review feedback. Verify it's correct for THIS codebase before changing anything.

The Response Pattern

WHEN receiving code review feedback:

1. READ    — Complete feedback without reacting
2. RESTATE — Summarize the requirement in your own words
3. VERIFY  — Check against actual codebase state
4. EVALUATE — Is this technically sound for THIS context?
5. RESPOND — Technical acknowledgment OR reasoned pushback
6. IMPLEMENT — One item at a time, verify each change

Forbidden Responses

NEVER say:

  • "You're absolutely right!" (without verification)
  • "Great catch!" (before confirming it IS a catch)
  • "I'll fix that right away!" (before evaluating whether it needs fixing)
  • "Done!" (without running verification — see skill-verification-gate)

These are social performance, not technical evaluation. They lead to:

  • Implementing wrong suggestions
  • Introducing bugs to "fix" non-issues
  • Wasting time on style preferences disguised as bugs

Evaluation Checklist

For each piece of feedback:

QuestionIf YESIf NO
Is the issue real? (verify in code)Continue evaluationPush back with evidence
Does the suggested fix work here?Continue evaluationPropose alternative
Does fixing this break something else?Fix both or push backImplement the fix
Is this a style preference or a real problem?Acknowledge, deprioritizeFix it
Was this already considered and rejected?Explain the trade-offImplement

How to Push Back

When feedback is wrong or doesn't apply:

markdown
> Reviewer: "This function should handle null input"
>
> Response: "Checked — this function is only called from `processUser()`
> (line 47) which validates non-null before dispatch. Adding null handling
> here would be dead code. The caller contract guarantees non-null."

Provide:

  1. What you checked
  2. Why the suggestion doesn't apply
  3. Evidence (line numbers, call sites, tests)

Multi-Provider Review Context

In Claude Octopus workflows, review feedback comes from multiple sources:

  • Codex review — tends toward enterprise patterns, may over-engineer
  • Antigravity review — tends toward ecosystem conformity, may suggest unnecessary dependencies
  • Claude review — tends toward elegance, may under-engineer error handling
  • Sonnet review — tends toward thoroughness, may flag low-priority issues

When providers disagree:

  • Check which provider's suggestion matches the ACTUAL codebase conventions
  • The codebase's existing patterns win over any provider's preferences
  • If two providers flag the same issue, it's probably real
Show full SKILL.md (160 more words)Show less

Handling Feedback Loops

When a reviewer flags an issue and you fix it:

  1. Make the fix
  2. Run verification (skill-verification-gate) — prove the fix works
  3. Re-read the original feedback — did you address the root cause or just the symptom?
  4. If the reviewer re-reviews and finds new issues, that's normal — don't get frustrated
  5. Each round should have FEWER issues, not different ones

If the same issue keeps coming back:

  • You're fixing symptoms, not the root cause
  • Stop and re-read the feedback from scratch
  • Ask the reviewer to clarify if the issue is ambiguous

When Review Feedback Conflicts with Requirements

If a reviewer suggests something that contradicts the spec/requirements:

  1. Note the conflict explicitly
  2. Check if the spec is wrong (it might be)
  3. If spec is correct: implement the spec, note the reviewer's concern for future consideration
  4. If spec is wrong: flag to the user before changing anything

Requirements trump review suggestions. User intent trumps both.

© nyldn, MIT. 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 skills/skill-review-response of nyldn/claude-octopus.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit b34780d

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in nyldn/claude-octopus, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Skill Review Response 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.

Skill Review Response compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skill Review Response this skillnyldn/claude-octopus4.2k1 repos~1.1kAutomated safety check: PassMIT
Review ResponseGalaxy-Dawn/claude-scholar5.7k2 repos~1.4kAutomated safety check: PassMIT
Nature Reviewer ResponseYuan1z0825/nature-skills47k—~1.5kAutomated safety check: PassApache-2.0
Review Pending PR Reviewsnrwl/nx29k—~3.9kAutomated safety check: PassMIT
Responsive Unitsthedaviddias/Front-End-Checklist74k—~472Automated safety check: PassMIT
Reviewthedaviddias/Front-End-Checklist74k—~556Automated safety check: PassMIT

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Questions about Skill Review Response

What does Skill Review Response do?

A skill your agent uses when a reviewer, CI bot, or another AI leaves feedback to address. Skill Review Response is an agent skill from nyldn/claude-octopus.

When should I use Skill Review Response?

Skill Review Response fits situations like: another AI leaves feedback to address.

How do I install Skill Review Response in Claude Code?

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

How do I install Skill Review Response in Codex?

Run `npx skills add nyldn/claude-octopus --skill skill-review-response -a codex`. Or copy the skill folder (skills/skill-review-response in nyldn/claude-octopus) into .agents/skills/skill-review-response in your project. Codex loads it when a task matches its description.

Can I use Skill Review Response 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 nyldn/claude-octopus --skill skill-review-response -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-review-response, .gemini/skills/skill-review-response, .github/skills/skill-review-response and .opencode/skills/skill-review-response in your project.

What does Skill Review Response need to run?

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

Does Skill Review Response 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 Skill Review Response 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 Skill Review Response use?

Skill Review Response 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 Skill Review Response use?

About 1.1k tokens (SKILL.md is roughly 4.4k 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 Skill Review Response?

Skills that share tags, products or a category with Skill Review Response: Review Response (Galaxy-Dawn/claude-scholar, 5.7k stars), Nature Reviewer Response (Yuan1z0825/nature-skills, 47k stars), Review Pending PR Reviews (nrwl/nx, 29k stars) and Responsive Units (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Review Response?

nyldn (a GitHub user) maintains it in nyldn/claude-octopus, which has 4,198 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on October 9, 2026.

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