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 skills add CarbeneAI/Forge --skill peerscangit clone --depth 1 https://github.com/CarbeneAI/ForgeWrote 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/carbeneai/forge/peerscan)<a href="https://agentmods.dev/skills/carbeneai/forge/peerscan"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/peerscan/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/carbeneai/forge/peerscan"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/peerscan.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 | $0.00047 | $0.00263 |
| Opus 5 | $0.00023 | $0.00131 |
| Sonnet 5 | $0.00009 | $0.00053 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
PeerScan 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 6d 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.
What it actually says
PeerScan
Scans a GitHub user's pull request history for a repository and generates a structured evidence report useful for engineering team assessments, consulting engagements, and performance reviews.
Workflow Routing
| Workflow | Trigger | File |
|---|---|---|
| Scan | "scan PRs", "peer scan", "review activity" | workflows/Scan.md |
Examples
Example 1: Scan a developer's PR history
User: "Scan @johndoe's PRs in acme/backend for the last 6 months"
→ Fetches all PRs via gh CLI
→ Analyzes volume, themes, quality signals
→ Generates structured report
→ Saves to Obsidian vault
Example 2: Client team assessment
User: "Assess the engineering activity for the 3 senior devs at client X"
→ Launches parallel PeerScan agents per developer
→ Generates comparison report
→ Identifies strengths and growth areas
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 34 lines · 47 tokens per session scan A 0312ab56f742
PeerScan is a skill published in the GitHub repository CarbeneAI/Forge (9 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 263 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
implementing-secret-scanning-with-gitleaks
This skill covers implementing Gitleaks for detecting and preventing hardcoded secrets in git repositories. It addresses configuring pre-commit hooks, CI/CD pipeline integration, custom rule authoring for organization-specific secrets, baseline management for existing repositories, and remediation workflows for…
vellum-github-app-setup
Create and configure a GitHub App so the assistant can push commits, open PRs, and comment under its own bot identity. Use when the user wants the assistant to have its own GitHub identity, or when setting up git push access for the first time.
mx-pr
Draft a pull request from the feature spec and git log, run an autonomous commit-history cleanup (content check), then publish to GitHub or GitLab (Bitbucket experimental) — or hand off. Use when a feature branch is ready for PR, standalone or from mx-flow. Usage: /mx-pr [name].
mx-commit
Commit all pending changes as one commit per logical concern, following the project's message convention (type prefix, 50-char subject, English). Use when the working tree may hold several changes or the convention must be enforced; a single trivial change can use plain git commit. Usage: /mx-commit [--auto].
summarize-changes
Summarizes uncommitted changes and flags anything risky.
public-release-prep
Audit a private git repository for secrets and personally-identifying info before it goes public, then carry out the cleanup. Use this whenever the user wants to open-source a repo, flip a GitHub repo from private to public, "clean up before going public," or asks whether a repo is safe to share externally — even if…