Borrowing it
Nothing to install: this file belongs to Parslee-ai/neo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Parslee-ai/neo/main/.claude/commands/gh-review-assess.mdgit clone --depth 1 https://github.com/Parslee-ai/neoWrote 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.
[](https://agentmods.dev/commands/parslee-ai/neo/gh-review-assess)<a href="https://agentmods.dev/commands/parslee-ai/neo/gh-review-assess"><img src="https://agentmods.dev/badge/commands/parslee-ai/neo/gh-review-assess/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.
<a href="https://agentmods.dev/commands/parslee-ai/neo/gh-review-assess"><img src="https://agentmods.dev/badge/commands/parslee-ai/neo/gh-review-assess.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00093 | $0.15446 |
| Opus 5 | $0.00046 | $0.07723 |
| Sonnet 5 | $0.00019 | $0.03089 |
| Haiku 4.5 | $0.00009 | $0.01545 |
Grade A, and why
gh-review-assess 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 1,613 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Usage
/gh-review-assess <comment_url>
Where:
comment_url(required): GitHub PR comment, review comment, or full review URL
Examples
Example 1: Basic Assessment of Single Comment
Scenario: You receive a code review comment suggesting that you refactor a working function to use a more "elegant" pattern. You want to assess whether this feedback is valuable or just stylistic preference.
Command:
/gh-review-assess https://github.com/acme/project/pull/456#issuecomment-789012
Expected Behavior:
- Fetches the comment content from GitHub using gh CLI
- Presents the comment to @agent-Linus for evaluation
- Linus categorizes the feedback as legitimate vs nitpicking
- For legitimate issues, @agent-linus-kernel-planner creates a simple implementation plan
- Returns structured summary showing accepted/rejected issues with rationale
Output:
REVIEW ASSESSMENT COMPLETE
=========================
Original Comment:
"This function should use map/reduce instead of a for loop. It's more functional."
LINUS EVALUATION:
Status: REJECTED
Category: Style Nitpicking
Rationale: The existing for loop is clear, performant, and maintainable.
Changing to map/reduce provides no tangible benefit and may reduce readability
for team members less familiar with functional patterns. This is textbook
bikeshedding.
VERDICT: No action required.
Notes:
- If the comment contains multiple distinct issues, Linus will evaluate each separately
- The command uses gh CLI's JSON API to fetch comment metadata and content
- Authentication is required via
gh auth loginbefore first use
Example 2: Multi-Issue Review with Mixed Validity
Scenario: A reviewer posts a comment with five separate concerns. Some are valid security issues, others are stylistic preferences. You need to quickly determine which ones deserve attention.
Command:
/gh-review-assess https://github.com/acme/backend/pull/234#issuecomment-567890
Expected Behavior:
- Extracts all distinct issues from the comment
- Linus evaluates each issue independently
- Valid issues are passed to linus-kernel-planner
- Returns comprehensive breakdown showing decisions for each issue
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.
- 12d ago First seen · 1,613 lines · 93 tokens per session scan A 5c55e5a60851
gh-review-assess is a command published in the GitHub repository Parslee-ai/neo (16 stars, last pushed 4d ago), licensed Apache-2.0. It adds 93 tokens to every session and 15,446 once invoked, about $0.0005 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 2026-08-30.
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