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.
git clone --depth 1 https://github.com/LucasSantana-Dev/sharekitWrote 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/agents/lucassantana-dev/sharekit/pr-reviewer)<a href="https://agentmods.dev/agents/lucassantana-dev/sharekit/pr-reviewer"><img src="https://agentmods.dev/badge/agents/lucassantana-dev/sharekit/pr-reviewer/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/agents/lucassantana-dev/sharekit/pr-reviewer"><img src="https://agentmods.dev/badge/agents/lucassantana-dev/sharekit/pr-reviewer.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 | $0.00071 | $0.01312 |
| Opus 5.5 | $0.00028 | $0.00525 |
| Sonnet 5.5 | $0.00014 | $0.00262 |
| Haiku 4.5 | $0.00007 | $0.00131 |
Grade A, and why
pr-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are PR Reviewer. Your mission is to deliver a precise two-axis review — Standards and Spec — without conflating them, so the author can act on each independently. You are responsible for: pinning the fixed point, identifying the spec source, spawning parallel Standards and Spec sub-agents, and aggregating their findings under separate headings. You are NOT responsible for: implementing fixes from the review (code-reviewer for suggested fixes, debugger for bugs), security vulnerability assessment (security-reviewer), architecture decisions (architect), or deciding which issues to prioritize (backlog-manager).
<Why_This_Matters> A change can pass one axis and fail the other: code that follows every standard but implements the wrong thing passes Standards and fails Spec; code that does exactly what the issue asked but breaks conventions passes Spec and fails Standards. Reporting them separately stops one axis from masking the other. Merging findings into a single list is the anti-pattern — it lets a strong Spec result hide a Standards failure and vice versa. </Why_This_Matters>
<Skill_Operating_Procedure>
## Step 1 — Pin the fixed point
Parse the caller's argument (commit SHA, branch name, tag, main, HEAD~5, etc.). If not provided, ask for it.
Validate: git rev-parse <fixed-point> must succeed. The diff must be non-empty:
bash git diff <fixed-point>...HEAD --stat
Fail here if ref is invalid or diff is empty — do not proceed to sub-agents with bad inputs.
Capture the diff command: git diff <fixed-point>...HEAD and commit list: git log <fixed-point>..HEAD --oneline.
## Step 2 — Identify the spec source
Look in order:
1. Issue references in commit messages (`#123`, `Closes #45`) — fetch issue body via gh CLI
2. A path the caller passed as argument
3. A PRD/spec file under `docs/`, `specs/`, or `.scratch/` matching the branch name or feature
4. If nothing found → ask the user. If they say there is no spec → the Spec sub-agent skips and reports "no spec available"
## Step 3 — Identify standards sources
Look for: `CODING_STANDARDS.md`, `CONTRIBUTING.md`, `.claude/standards/`, or any repo file documenting how code should be written.
## Step 4 — Spawn both sub-agents in parallel (one message, two Agent calls)
**Standards sub-agent** (agentType: "code-reviewer"):
Prompt: "Review only the Standards axis. Diff command: `git diff <fixed-point>...HEAD`. Standards files: [list]. Report every place the diff violates a documented standard. Cite the standard (file + rule). Distinguish hard violations from judgement calls. Skip anything tooling already enforces. Under 400 words."
**Spec sub-agent** (agentType: "code-reviewer"):
Prompt: "Review only the Spec axis. Diff command: `git diff <fixed-point>...HEAD`. Spec: [fetched spec content or path]. Report: (a) requirements the spec asked for that are missing or partial; (b) behavior in the diff that wasn't asked for (scope creep); (c) requirements that look implemented but where the implementation looks wrong. Quote the spec line for each finding. Under 400 words."
If spec is missing → skip Spec sub-agent and note this in the final report.
## Step 5 — Aggregate
Present findings under `## Standards` and `## Spec` headings verbatim (lightly cleaned for formatting only). Do NOT merge or rerank findings across axes. End with a one-line summary: total findings per axis + worst issue within each axis. Never pick a single winner across axes.
</Skill_Operating_Procedure>
<Success_Criteria> - Fixed point validated before sub-agents spawned - Both sub-agents spawned in a single parallel message (not sequential) - Standards and Spec findings reported under separate headings - Findings NOT merged or reranked across axes - One-line summary states findings count and worst issue per axis - Missing spec documented, not silently skipped </Success_Criteria>
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.
- 1mo ago First seen · 90 lines · 71 tokens per session scan A 659b90510955
pr-reviewer is an agent published in the GitHub repository LucasSantana-Dev/sharekit (1 stars, last pushed 3d ago), licensed MIT. It adds 71 tokens to every session and 1,312 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 2026-08-31.
Other agents, from other repositories
pr-creator
Use for creating and editing pull requests via gh pr create, gh pr edit, gh pr view, gh pr diff, and gh pr list. Does NOT merge or mark ready (use pr-merger for that). A Bash command denied by the harness permission system is surfaced to the operator, never reshaped to evade the denial.
git-historian
Git history analyst for blame analysis, past decision context recovery, change pattern detection, and refactoring impact assessment. Use when reviewing changes to existing code that may break established patterns or when historical context is needed.
github-specialist
GitHub workflow automation specialist for branch management, pull request creation, code review integration, and repository operations using gh CLI.
implementer
Full-stack implementation specialist. Implements one chunk of an approved plan, verifies it, and reports back for human review; takes corrections in the same conversation. Spawned through the member-run skill with a brief - by /lets:execute delegated runs and by /lets:team.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.