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 commands/yonatangross/orchestkit/review-prgit clone --depth 1 https://github.com/yonatangross/orchestkitWrote 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/yonatangross/orchestkit/review-pr)<a href="https://agentmods.dev/commands/yonatangross/orchestkit/review-pr"><img src="https://agentmods.dev/badge/commands/yonatangross/orchestkit/review-pr.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 | $0.00069 | $0.06174 |
| Opus 5 | $0.00034 | $0.03087 |
| Sonnet 5 | $0.00014 | $0.01235 |
| Haiku 4.5 | $0.00007 | $0.00617 |
Grade A, and why
review-pr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 463 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto-generated from skills/review-pr/SKILL.md
Source: https://github.com/yonatangross/orchestkit
Review PR
Deep code review using 6-7 parallel specialized agents.
Quick Start
/ork:review-pr 123
/ork:review-pr feature-branch
Opus 5: Parallel agents use native adaptive thinking for deeper analysis. Complexity-aware routing matches agent model to review difficulty.
Argument Resolution
The PR number or branch is passed as the skill argument. Resolve it immediately:
PR_NUMBER = "$ARGUMENTS[0]" # e.g., "123" or "feature-branch"
# If no argument provided, check environment
if not PR_NUMBER:
PR_NUMBER = os.environ.get("ORCHESTKIT_PR_URL", "").split("/")[-1]
# If still empty, detect from current branch
if not PR_NUMBER:
PR_NUMBER = "$(gh pr view --json number -q .number 2>/dev/null)"
Use PR_NUMBER consistently in all subsequent commands and agent prompts.
STEP 0: Verify User Intent with AskUserQuestion
BEFORE creating tasks, clarify review focus:
AskUserQuestion(
questions=[{
"question": "What type of review do you need?",
"header": "Focus",
"options": [
{"label": "Full review (Recommended)", "description": "Security + code quality + tests + architecture"},
{"label": "Security focus", "description": "Prioritize security vulnerabilities"},
{"label": "Performance focus", "description": "Focus on performance implications"},
{"label": "Quick review", "description": "High-level review, skip deep analysis"}
],
"multiSelect": false
}]
)
Based on answer, adjust workflow:
- Full review: All 6-7 parallel agents
- Security focus: Prioritize security-auditor, reduce other agents
- Performance focus: Add frontend-performance-engineer agent
- Quick review: Single code-quality-reviewer agent only
"Ultra" mode → defer to claude ultrareview (CC 2.1.120+, #1542)
If the user asks for an "ultra" / "deep" / "thorough" review and the host is on CC ≥ 2.1.120, defer to the native subcommand instead of re-implementing the multi-agent loop in skill instructions:
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.
- 2d ago Changed 50a3b6e1307b
- 5d ago First seen · 463 lines · 69 tokens per session scan A e5ad1a0ca4ea
review-pr is a command published in the GitHub repository yonatangross/orchestkit (228 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 6,174 once invoked, about $0.0003 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
ralph-plan
../../.mastracode/commands/ralph-plan.md.
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
reset-handoff
Reset the agent handoff system by cleaning up state files and logs.
bug
Reproduce then TDD-fix a ready-for-agent bug ticket in this checkout. Web bugs get a browser repro first.
mempenny-memory-distill
Distill a single memory file in-place — replace prose narrative with 1-3 sentences of forward-looking truth. (opencode host adapter).
pn-distill
Remove content, sections, and features that don't earn their place — information architecture reduction. Use when there's too much stuff on the page. For visual decoration reduction, use pn-quieter.