streamlit: Skill for Claude Code

.claude/skills/addressing-pr-review-comments/SKILL.md

addressing-pr-review-comments is a skill for Claude Code from streamlit/streamlit. It costs 61 tokens per session (2,590 once invoked), scanned A, original, Apache-2.0.

A procedure for handling reviewer feedback on a GitHub pull request, which is a proposed code change. It covers both comments attached to specific lines and general comments on the pull request.

In plain words
What is it for?
Use it to inspect feedback on the current branch's Streamlit pull request, categorize actionable comments, and prepare code, style, or documentation fixes. It presents options before applying changes and can summarize replies to reviewers.
Why use it?
It prevents feedback from being missed by collecting both kinds of comments and tracking each step from review through possible fixes. It also requires checking GitHub access before starting.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is streamlit/streamlit's own configuration. It tells Claude Code how to work on streamlit itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything streamlit configures →

About the project

Streamlit is a Python framework that turns scripts into interactive web applications for data exploration, dashboards, reports, and chat interfaces. Data scientists, machine-learning practitioners, and developers use it to build and share data apps without implementing the web interface from scratch. The catalogue add-ons support coding-agent workflows for Streamlit applications.

streamlit/streamlit · 46,171 stars · on GitHub · streamlit.io

Reuse

Borrowing it

Nothing to install: this file belongs to streamlit/streamlit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/streamlit/streamlit/develop/.claude/skills/addressing-pr-review-comments/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/streamlit/streamlit

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
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Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,590 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Snyk warn 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.02590
Opus 5.5 $0.00024 $0.01036
Sonnet 5.5 $0.00012 $0.00518
Haiku 4.5 $0.00006 $0.00259

Measured 9d ago against content hash e5f57f275c22, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

addressing-pr-review-comments scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/addressing-pr-review-comments/SKILL.md · 251 lines

How it starts

The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Address PR Comments

Address actionable review comments on the PR for the current branch using gh CLI.

Workflow checklist

Copy and track progress:

- [ ] 1. Verify auth: gh auth status
- [ ] 2. Fetch PR data and comments
- [ ] 3. Analyze and categorize comments
- [ ] 4. Present options to user
- [ ] 5. Apply selected fixes
- [ ] 6. Show summary, next steps, and offer to post replies

1. Verify authentication

gh auth status

If auth fails, prompt user to run gh auth login.

2. Fetch PR data

You must fetch both inline review comments and general PR (issue) comments. Use both when building the list of feedback to address. General comments have no file or line. Treat them as PR-level feedback.

# PR details for current branch (extract PR number from here)
gh pr view --json number,title,url,state,author,headRefName,baseRefName,reviewDecision,reviews,comments

# Inline review comments with file/line info (--paginate fetches all pages)
gh api --paginate repos/streamlit/streamlit/pulls/{PR_NUMBER}/comments

# General PR discussion comments (--paginate fetches all pages)
gh api --paginate repos/streamlit/streamlit/issues/{PR_NUMBER}/comments

Get unresolved review threads via GraphQL (inline only; used for file/path/line). The query returns the first comment of each thread for display when listing threads; full comment bodies are already fetched via the REST pulls/{PR_NUMBER}/comments and issues/{PR_NUMBER}/comments APIs above. Note: reviewThreads(first: 100) returns at most 100 threads; for PRs with more unresolved threads, use cursor-based pagination (pageInfo.hasNextPage / endCursor) or rely on the REST comments list.

gh api graphql -f query="
{
  repository(owner: \"streamlit\", name: \"streamlit\") {
    pullRequest(number: {PR_NUMBER}) {
      reviewThreads(first: 100) {
        nodes {
          id
          isResolved
          path
          line
          comments(first: 1) {
            nodes { author { login } body }
          }
        }
      }
    }
  }
}" --jq '[.data.repository.pullRequest.reviewThreads.nodes[] | select(.isResolved == false)]'

Read the full file on GitHub · 251 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago Changed · +2 lines e5f57f275c22
  2. 2mo ago First seen · 249 lines · 61 tokens per session scan A f54fd8348913

Subscribe to this mod's changes

addressing-pr-review-comments is a skill published in the GitHub repository streamlit/streamlit (46,171 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 2,590 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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