pr-review-canvas-html

pr-review-canvas-html is a skill for Claude Code, Codex from OutlineDriven/odin-claude-plugin. It costs 58 tokens per session (1,538 once invoked), scanned A, original, Apache-2.0.

A local HTML view of a GitHub pull request, including its changes, comments, and detected moved code. A pull request is a proposed set of changes submitted for review.

In plain words
What is it for?
Use it to render a GitHub pull request into an HTML review page served on your computer.
Why use it?
It makes a pull request easier to inspect as a standalone page and highlights code changes that may deserve closer attention.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the odin-create-advanced plugin — 16 skills shipped together

Good fit Use it to render a GitHub pull request into an HTML review page served on your computer.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add OutlineDriven/odin-claude-plugin --skill pr-review-canvas-html
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/odin-claude-plugin

Made for: Claude Code, Codex.

Or install odin-create-advanced, the plugin that ships this one along with the rest of its 16 skills.

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.

agentmods badge for pr-review-canvas-html

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html/github.svg)](https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html/github.svg" alt="Measured on agentmods" height="20"></a>

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.

agentmods 80×15 button for pr-review-canvas-html

Your own site · 80×15
<a href="https://agentmods.dev/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-claude-plugin/pr-review-canvas-html.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,538 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
  • 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 $0.00058 $0.01538
Opus 5 $0.00029 $0.00769
Sonnet 5 $0.00012 $0.00308
Haiku 4.5 $0.00006 $0.00154

Measured 6d ago against content hash 0548f9bbd2b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

pr-review-canvas-html 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 6d 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.

plugins/odin-create-advanced/skills/pr-review-canvas-html/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PR review canvas HTML

Contract

Field Bound contract
Trigger Render a GitHub PR as standalone review HTML.
Authority Reversible-local: writes confined to /tmp. No VCS, credential, paid, published, deployed, or remote mutation.
Side effect Writes one self-contained HTML file to /tmp and serves it on a fixed localhost port.
Done A self-contained HTML artifact at /tmp/pr-review-.html, served on localhost.

Inputs

  • PR URL or identifier (required): a GitHub PR web URL or owner/repo#<number>. The model extracts {owner}, {repo}, {number}.
  • PR data (fetched): gh api repos/{owner}/{repo}/pulls/{number}, file list, diff, and comments fetched during step 2.

Procedure

  1. Parse the PR identifier. Extract {owner}, {repo}, {number} from the provided URL or owner/repo#number string. Stop if extraction fails. Done when: owner, repo, and number are extracted.

  2. Fetch PR data in parallel. Run these gh api calls concurrently:

    gh api repos/{owner}/{repo}/pulls/{number} --jq '{title, body, user: .user.login, state, additions, deletions, changed_files, base: .base.ref, head: .head.ref}'
    gh api repos/{owner}/{repo}/pulls/{number}/files --paginate --jq '.[] | {filename, status, additions, deletions, patch}'
    gh api repos/{owner}/{repo}/pulls/{number}/comments --jq '.[] | {user: .user.login, body, path, line}'
    

    Stop if any call fails or returns no data. Done when: all three API calls return data.

  3. Analyze the PR and write body HTML. Read the diffs, understand the PR, and write the <body> content directly as HTML. Use any structure that fits the PR: a header with title, PR number, author, and stats; a summary box explaining the PR in plain English; core file sections with annotations and diffs; boilerplate files collapsed by default; a review checklist at the bottom. Include <div data-diff="<target>"> placeholders where diffs should render. Add collapsible boilerplate sections, inline code references, and callout boxes for warnings. Done when: the body HTML is written with data-diff placeholders for every diff target.

Read the full file on GitHub · 99 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 6d ago First seen · 99 lines · 58 tokens per session scan A 0548f9bbd2b7

Subscribe to this mod's changes

pr-review-canvas-html is a skill published in the GitHub repository OutlineDriven/odin-claude-plugin (35 stars, last pushed yesterday), licensed Apache-2.0. It adds 58 tokens to every session and 1,538 once invoked, about $0.0003 per session on Opus 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 2026-09-04.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens