assess-pr

assess-pr is a skill for Claude Code from bjcoombs/ai-native-toolkit. It costs 67 tokens per session (9,430 once invoked), scanned A, original, Apache-2.0.

The end-of-run step for `/assess`, a codebase assessment workflow. It offers ways to share the report, track its three main actions, turn it into a continuous-integration check, submit feedback, or remove the files it created.

In plain words
What is it for?
It helps open a pull request, create issue-tracker items, freeze assessment rules into CI, report tool problems, or uninstall the assessment output.
Why use it?
It gives assessment results a follow-up path instead of leaving them as a report that nobody acts on.

Skill for Claude Code

Written for Claude Code: ${CLAUDE_SKILL_DIR} variable. Also seen: reads .claude/ paths; mentions CLAUDE.md; names the AskUserQuestion tool.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is Full report: [`.assess/assess-report.md`](./.assess/assess-report.md) (the heatmap and doc graph render inline)..

Part of the ai-native-toolkit plugin — 19 skills, 8 agents shipped together

Good fit It helps open a pull request, create issue-tracker items, freeze assessment rules into CI, report tool problems, or uninstall the assessment output.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/bjcoombs/ai-native-toolkit
agentmods
npx agentmods add skills/bjcoombs/ai-native-toolkit/assess-pr

Made for: Claude Code.

Or install ai-native-toolkit, the plugin that ships this one along with the rest of its 19 skills, 8 agents.

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 assess-pr

README.md
[![agentmods](https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess-pr/github.svg)](https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess-pr)
Your own site
<a href="https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess-pr"><img src="https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess-pr/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 assess-pr

Your own site · 80×15
<a href="https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess-pr"><img src="https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,430 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.
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 $0.00067 $0.09430
Opus 5.5 $0.00027 $0.03772
Sonnet 5.5 $0.00013 $0.01886
Haiku 4.5 $0.00007 $0.00943

Measured 1mo ago against content hash 11c8c76a1a70, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

assess-pr 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 1mo 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.

skills/assess-pr/SKILL.md · 405 lines

How it starts

The opening of the file, as written. The whole thing — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assess PR and Issues

The end-of-run half of /assess. The report (.assess/assess-report.md), the complexity heatmap, and the doc graph are written. This step runs the optional end-of-run offers - in order - then closes the loop:

  1. Open a PR with the report (Step 5).
  2. Track the Top 3 Actions in the user's issue tracker (Step 6).
  3. Freeze the assessment into a CI gate (Step 6.5).
  4. Tool feedback (Step 7) - surface anomalies and offer to file feedback.
  5. Uninstall /assess (Step 8) - the escape hatch: remove everything this run wrote.

Each offer is independent (uninstall excepted - it's mutually exclusive with the write-back offers): a user can accept any subset. The step references back into the written assess-report.md artifact (notably the Top 3 Actions table's Issue column), not into the scoring prose, so it stays decoupled from how the report was produced.

Phase 2: ask once, batched (and the non-interactive contract)

These are the write-back phase of the consent lifecycle (Phase 2; Phase 1 was the tool installs, Phase 3 the mutation pass - see the assess SKILL.md). Do not serialise them into back-to-back modals. Present them as one batched, multi-select AskUserQuestion: "Now that the report is written, which of these should I do?" with the options (open a PR, track the Top 3 Actions, freeze a CI gate, file feedback, and - the mutually-exclusive escape hatch - uninstall /assess from this repo), pre-filtered by feasibility:

  • Drop the PR option when the push-capability / remote check below (Step 5) shows no direct or fork PR is possible; on a read-only target, offer the fork variant instead. When the target states it takes no contributions (Step 5's no-contributions scan), offer the no-contributions variant instead on a read-only target (READ / TRIAGE) or in a clone of the user's own fork: a PR inside the user's fork, never one against upstream. A user who can push to the non-fork repo itself keeps the direct PR option, with the statement quoted.
  • Drop the CI gate option when the workflow could never run (no GitHub remote).
  • Keep issue tracking and feedback always (feedback needs no repo write).
  • Uninstall (Step 8) always appears: it removes what this run wrote. It doesn't compose with the write-back offers (no point opening a PR and deleting the report), so treat selecting it as "skip the others and clean up".

Read the full file on GitHub · 405 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. 1mo ago Changed · -4 lines 11c8c76a1a70
  2. 1mo ago Changed · +65 lines 69304f48a66b
  3. 1mo ago First seen · 344 lines · 67 tokens per session scan A 1b6c42f0cb86

Subscribe to this mod's changes

assess-pr is a skill published in the GitHub repository bjcoombs/ai-native-toolkit (32 stars, last pushed 5d ago), licensed Apache-2.0. It adds 67 tokens to every session and 9,430 once invoked, about $0.0003 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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