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.
npx agentmods add skills/juandarn/pr-description-skill/pr-descriptionnpx skills add juandarn/pr-description-skill --skill pr-descriptiongit clone --depth 1 https://github.com/juandarn/pr-description-skillWrote 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/juandarn/pr-description-skill/pr-description)<a href="https://agentmods.dev/skills/juandarn/pr-description-skill/pr-description"><img src="https://agentmods.dev/badge/skills/juandarn/pr-description-skill/pr-description.svg" alt="Measured on agentmods" 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 | $0.00053 | $0.03648 |
| Opus 5 | $0.00026 | $0.01824 |
| Sonnet 5 | $0.00011 | $0.00730 |
| Haiku 4.5 | $0.00005 | $0.00365 |
Grade A, and why
pr-description scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**Private-repo note**: an anonymous `curl` of the asset URL returns 404 — do not interpret this as a broken upload. The asset renders correctly for any logged-in reviewer with repo access (served same-origin, not via the How it starts
The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Description Generator
When creating or updating a pull request, ALWAYS generate a comprehensive, visual description following the format below. The goal is that a reviewer can understand the entire PR in under 60 seconds by scanning diagrams and bold titles.
Process
- Identify the base branch (usually
masterormain) - Read ALL commits in the branch:
git log --oneline <base>..HEAD - Read the full diff against base:
git diff <base>...HEAD --statfor an overview - Read the actual code changes for key files:
git diff <base>...HEAD -- <file>to understand the logic - Categorize changes into: Features, Bug Fixes, Performance, UI/UX, Refactoring, Testing, Documentation
- Create Mermaid diagrams to visualize the changes (see Diagram Guidelines below)
- Write the description in English regardless of the conversation language
PR Description Template
## Summary
[1-3 bullet points explaining WHAT changed and WHY, in plain language]
## Diagrams
### [Diagram title - e.g., "Data Flow", "Bug -> Fix", "Architecture Change"]
```mermaid
[Appropriate diagram type - see Diagram Guidelines]
```
### [Additional diagram if needed - e.g., "Code Changes", "State Machine"]
```mermaid
[Additional diagram]
```
## Changes
### [Category 1] (e.g., Features, Bug Fixes, Performance)
- **[Change title]** - brief explanation of what and why
- **[Change title]** - brief explanation of what and why
### [Category 2]
- ...
## Code Changes (key files)
```mermaid
flowchart LR
subgraph "filename.ts"
A["line X:<br/><s>old code</s>"] --> B["new code"]
end
```
## Test Plan
- [x] [Automated test that passes - with count if applicable]
- [x] [Another automated test]
- [ ] [Manual test step to verify]
- [ ] [Another manual verification]
### What type of PR is this?
- [ ] Refactor
- [ ] Feature
- [ ] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Testing Coverage
- [ ] Other
## Evidence (Before/After)
<!-- Backend / API / service — run locally, exercise with real requests, capture stdout/responses, render to PNG: -->

<!-- UI — run the app locally, drive the real screen with Playwright, screenshot actual rendered UI: -->
| Before | After |
|--------|-------|
|  |  |
<!-- New component — no prior screen exists, after-only: -->

<!-- CLI / hooks / scripts — run the real command, capture real output, screenshot it: -->

<!-- Fallback only when the service genuinely cannot be run locally (hard external deps, secrets): capture from a real deployed run or emit an explicit placeholder for the author — NEVER invent or mock the image: -->
| Before | After |
|--------|-------|
| _[author: attach REAL BEFORE screenshot here — no mocks]_ | _[author: attach REAL AFTER screenshot here — no mocks]_ |
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.
- 3d ago First seen · 326 lines · 53 tokens per session scan A 65a0359d39e0
pr-description is a skill published in the GitHub repository juandarn/pr-description-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 3,648 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…