Borrowing it
Nothing to install: this file belongs to israel-salgado/dt-mcp-server. 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/israel-salgado/dt-mcp-server/main/.agents/skills/pr-review/SKILL.mdgit clone --depth 1 https://github.com/israel-salgado/dt-mcp-serverWrote 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/skills/israel-salgado/dt-mcp-server/pr-review)<a href="https://agentmods.dev/skills/israel-salgado/dt-mcp-server/pr-review"><img src="https://agentmods.dev/badge/skills/israel-salgado/dt-mcp-server/pr-review/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/skills/israel-salgado/dt-mcp-server/pr-review"><img src="https://agentmods.dev/badge/skills/israel-salgado/dt-mcp-server/pr-review.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 | $0.00082 | $0.02135 |
| Opus 5 | $0.00041 | $0.01068 |
| Sonnet 5 | $0.00016 | $0.00427 |
| Haiku 4.5 | $0.00008 | $0.00214 |
Grade A, and why
pr-review 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 11d 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.
This is a copy
86% identical to pr-review — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Quality Review
Perform a comprehensive quality review of a pull request or feature branch. This skill covers production readiness, code quality, UX, documentation, tests, and safety.
The review is structured as a checklist across seven dimensions. For each dimension, investigate the actual code and report specific findings -- not just "looks good" but concrete observations with file paths and line numbers.
Getting Started
First, understand the scope of the change:
# What branch are we on, what's the base?
git branch --show-current
git log main..HEAD --oneline
# What files changed?
git diff main...HEAD --stat
# Full diff for review
git diff main...HEAD
If reviewing a remote PR, fetch it first:
gh pr view <number> --json title,body,files
gh pr diff <number>
Read the PR description and all commits to understand the intent before diving into code.
Review Dimensions
Work through each dimension below. For each one, report a status:
- Pass -- meets the bar, no issues
- Needs work -- specific issues found (list them)
- N/A -- not applicable to this change
1. Production Readiness
Does this code behave correctly and handle failure gracefully?
- Error handling: Are all errors checked? Are they wrapped with context (
fmt.Errorf("context: %w", err))? Do they surface actionable messages to users? - Edge cases: Empty inputs, nil values, missing config, network failures, API rate limits, large datasets, pagination boundaries
- Safety checks: All mutating commands (create, edit, apply, delete, update) must include safety checks after
LoadConfig()and before client operations. Pattern:
Verify correct operation type. Skip only in dry-run paths.checker, err := NewSafetyChecker(cfg) if err := checker.CheckError(safety.OperationXXX, safety.OwnershipUnknown); err != nil { return err } - No stdout in library code:
pkg/must return data, not print. Onlycmd/handles output. - No hardcoded secrets or customer data: No real names, env IDs, tokens, or emails in code or tests. Use
@example.invalidfor emails (RFC 2606).
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.
- 11d ago First seen · 200 lines · 82 tokens per session scan A 16793b5acd3e
pr-review is a skill published in the GitHub repository israel-salgado/dt-mcp-server (2 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 2,135 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to pr-review, differing in 4 lines, and is treated as a copy.
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