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Agent skill

PR Feedback

by strands-agents in strands-agents/harness-sdk

Fetches PR review feedback and inline comments, categorizes them, and presents options to the user.

Apache-2.0Auto-check passedDevelopment

Install PR Feedback

skills CLI
$ npx skills add strands-agents/harness-sdk --skill pr-feedback -a claude-code

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

GitHub CLI
$ gh skill install strands-agents/harness-sdk pr-feedback --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/strands-agents/harness-sdk.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/pr-feedback .claude/skills/pr-feedback && 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
pr-feedback
GitHub stars
8.7k
Token cost
~675 tokens
SKILL.md length
346 words
Files
2
Skills in repo
14
Repo updated
First seen
Licence
Apache-2.0

At a glance

Fetches PR review feedback and inline comments, categorizes them, and presents options to the user.

  • Works in 4 steps: Determine the PR Number → Fetch All Feedback → Summarize and Present to the User → …
  • The user asks to get
  • SKILL.md covers Process and Rules
  • Runs Shell scripts from its folder; calls gh and bash

What it does

PR Feedback is an agent skill from strands-agents/harness-sdk. Fetches PR review feedback and inline comments, categorizes them, and presents options to the user. Use when the user asks to get, read, address, or fix review comments on a pull request.

Its SKILL.md is about 680 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `fetch-pr-feedback.sh`).

It sits in Development, covering Pull requests and Technical documentation. The repository describes itself as: Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud. The licence is Apache-2.0.

When your agent uses it

  • The user asks to get
  • Fix review comments on a pull request

Example prompts

  • “Use the pr-feedback skill to fetch PR review feedback and inline comments, categorizes them, and presents options to the user”
  • “/pr-feedback”

Requirements

  • A Bash shell

Workflow steps

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

  1. Determine the PR Number
  2. Fetch All Feedback
  3. Summarize and Present to the User
  4. Fix What the User Selects

What it can do on your machine

Read from SKILL.md and the folder at commit e519d67. 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

    Ships script files (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • gh
    • bash

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

  • Network

    No URLs in SKILL.md. Its commands use gh, 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

PR Feedback loads about 675 tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 346 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~675

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 strands-agents/harness-sdk at commit e519d67, republished under its Apache-2.0 licence (© strands-agents). 346 words, ~675 tokens.

Download SKILL.mdSave it as .claude/skills/pr-feedback/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
pr-feedback
description
Fetches PR review feedback and inline comments, categorizes them, and presents options to the user. Use when the user asks to get, read, address, or fix review comments on a pull request.

PR Review Feedback

Fetch PR review feedback and inline comments, categorize them, and present options to fix.

Process

1. Determine the PR Number

Auto-detect from the current branch:

bash
gh pr view --json number -q .number

If that fails (detached HEAD, no tracking branch), ask the user for the PR number or URL.

2. Fetch All Feedback

Use the bundled script to fetch reviews, inline comments, and issue-level comments in one shot:

bash
bash .agents/skills/pr-feedback/fetch-pr-feedback.sh <number> [--repo owner/repo]
  • Omit <number> to auto-detect from the current branch.
  • Use --repo when the PR is in a different repo than the current directory.

The script returns JSON with three arrays:

  • reviews — top-level review summaries (non-empty bodies only)
  • inline_comments — unresolved thread comments with upvotes/downvotes arrays (usernames who reacted), outdated flag, and diffHunk on the first comment in each thread
  • comments — issue-level comments
3. Summarize and Present to the User

Read all the feedback, use your judgment to group related items, and present a numbered list of things to address. Keep each item to one line. Put the most impactful items first.

Use upvotes, downvotes, and the PR author's own replies to determine priority:

  • Upvoted by the PR author: This signals agreement — recommend fixing it.
  • Author replied agreeing (e.g. "good point", "I'll fix", "makes sense"): Same as an upvote — recommend fixing it.
  • Upvoted by other reviewers (not the author): Signals community agreement the issue matters — lean toward recommending.
  • No signal from the author: Present as a suggestion but don't assume it should be fixed.
  • Author replied disagreeing or explaining: Present for context but mark as "discussed — likely skip".
  • Outdated comments: Group separately at the end — these may have been addressed by subsequent pushes.

When presenting the list, annotate items you recommend fixing (based on the signals above) so the user can quickly confirm "all recommended" or cherry-pick.

4. Fix What the User Selects

Address only the confirmed items. After fixing, briefly note what changed — one line per item.

Rules

  • Always auto-detect the PR number before asking the user.
  • Never fix anything before presenting the list and getting user confirmation.
  • If the output is too large to parse in one shot, focus on non-outdated comments first.

© strands-agents, 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 1 other file in .agents/skills/pr-feedback of strands-agents/harness-sdk.

  • SKILL.md
  • fetch-pr-feedback.sh

Open the folder on GitHubat commit e519d67

Compare with similar skills

PR Feedback 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.

PR Feedback compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
PR Feedback this skillstrands-agents/harness-sdk8.7k—~675Automated safety check: PassApache-2.0
Post Draft Reviewagent-substrate/substrate4.5k—~2.8kAutomated safety check: PassApache-2.0
Review Kedro PRkedro-org/kedro11k—~2.8kAutomated safety check: PassCustom licence
Opik Documentation Patternscomet-ml/opik22k—~1.3kAutomated safety check: PassApache-2.0
Eli5coldteadotai/pr-lens1.9k—~2.3kAutomated safety check: PassMIT
Review PRjavierbrea/eslint-plugin-boundaries997—~2.9kAutomated safety check: PassMIT

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  • PR Create

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Categories

Questions about PR Feedback

What does PR Feedback do?

Fetches PR review feedback and inline comments, categorizes them, and presents options to the user. PR Feedback is an agent skill from strands-agents/harness-sdk. Fetches PR review feedback and inline comments, categorizes them, and presents options to the user.

When should I use PR Feedback?

PR Feedback fits situations like: the user asks to get; fix review comments on a pull request.

How do I install PR Feedback in Claude Code?

Run `npx skills add strands-agents/harness-sdk --skill pr-feedback -a claude-code`. Or copy the skill folder (.agents/skills/pr-feedback in strands-agents/harness-sdk) into .claude/skills/pr-feedback in your project. Claude Code loads it when a task matches its description.

How do I install PR Feedback in Codex?

Run `npx skills add strands-agents/harness-sdk --skill pr-feedback -a codex`. Or copy the skill folder (.agents/skills/pr-feedback in strands-agents/harness-sdk) into .agents/skills/pr-feedback in your project. Codex loads it when a task matches its description.

Can I use PR Feedback 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 strands-agents/harness-sdk --skill pr-feedback -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pr-feedback, .gemini/skills/pr-feedback, .github/skills/pr-feedback and .opencode/skills/pr-feedback in your project.

What does PR Feedback need to run?

Going by SKILL.md and its folder, PR Feedback needs a shell for the scripts in its folder and the command-line tools its instructions call (gh and bash). Our summary lists: A Bash shell.

Does PR Feedback access the network?

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

Is PR Feedback 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 PR Feedback use?

PR Feedback 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 PR Feedback use?

About 675 tokens (SKILL.md is roughly 2.7k 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 PR Feedback?

Skills that share tags, products or a category with PR Feedback: Post Draft Review (agent-substrate/substrate, 4.5k stars), Review Kedro PR (kedro-org/kedro, 11k stars), Opik Documentation Patterns (comet-ml/opik, 22k stars) and Eli5 (coldteadotai/pr-lens, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains PR Feedback?

strands-agents (a GitHub organization) maintains it in strands-agents/harness-sdk, which has 8,731 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 7, 2026.

Source: strands-agents/harness-sdk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.