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/sjungling/sjungling-claude-pluginsWrote 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/sjungling/sjungling-claude-plugins/monitor-prs)<a href="https://agentmods.dev/commands/sjungling/sjungling-claude-plugins/monitor-prs"><img src="https://agentmods.dev/badge/commands/sjungling/sjungling-claude-plugins/monitor-prs/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/sjungling/sjungling-claude-plugins/monitor-prs"><img src="https://agentmods.dev/badge/commands/sjungling/sjungling-claude-plugins/monitor-prs.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 | $0.00017 | $0.01074 |
| Opus 5 | $0.00009 | $0.00537 |
| Sonnet 5 | $0.00003 | $0.00215 |
| Haiku 4.5 | $0.00002 | $0.00107 |
Grade A, and why
monitor-prs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitor all open pull requests in the current repository. Designed for recurring use with /loop or as a one-shot check.
This command orchestrates PR monitoring. Expensive review work is delegated to specialized skills and agents that use their own models.
Setup
Determine the repository owner and name:
REPO=$(gh repo view --json nameWithOwner -q '.nameWithOwner')
Fetch all open PRs authored by the current user:
gh pr list --author "@me" --state open --json number,title,headRefName,updatedAt,mergeable
If no open PRs are found, report that to the user and stop.
Step 1: Identify PRs Needing Review
Track review state using a timestamp file at /tmp/monitor-prs-last-run-{repo-slug}.txt. If the file exists, read the ISO 8601 timestamp from it. If it does not exist, treat all PRs as needing review.
Filter to PRs whose updatedAt is newer than the last-run timestamp (or all PRs on the first run). Skip unchanged PRs for review, but still include them in conflict and comment checks (Steps 4-5).
Step 2: Review New or Updated PRs
For each PR that needs review, invoke the /pr-review-toolkit:review-pr skill using the Skill tool:
Skill: "pr-review-toolkit:review-pr"
Args: "{number}"
This delegates the full code review (diff analysis, finding issues, confidence scoring, validation) to the specialized review toolkit, which uses its own model and agent pipeline.
Wait for the review to complete before proceeding. The skill will produce validated review findings.
Step 3: Post Review Comments
If the review from Step 2 produced any findings, use the /workflow:post-pr-comments skill to post them on the PR:
Skill: "workflow:post-pr-comments"
Invoke the skill once per PR that has findings. The skill handles formatting comments, resolving line numbers, and posting via the GitHub API.
If no findings were produced, skip to Step 4.
Step 4: Check for Merge Conflicts
For each open PR, check the mergeable field from the PR list query:
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.
- 10d ago First seen · 125 lines · 17 tokens per session scan A 8479be843094
monitor-prs is a command published in the GitHub repository sjungling/sjungling-claude-plugins (13 stars, last pushed 27d ago), licensed MIT. It adds 17 tokens to every session and 1,074 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
devkit.github.review-pr
Provides comprehensive GitHub pull request review with code quality, security, and best practices analysis. Use when reviewing a PR before merging.
speckit.spex.submit
Push and create PR for team review, with optional watch mode for CI monitoring.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
code-review
Code review for branch changes. Analyzes git diff between branches with multi-level depth (low/medium/high). Matches changes against task description. Returns structured report with severity levels and verdict.
advanced-code-review-context
Advanced Code Review Phase 2: Context Analysis - load previous reviews, PR history, declined items.