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 zacharygcook/agent-skills --skill ralph-reviewgit clone --depth 1 https://github.com/zacharygcook/agent-skillsWrote 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/zacharygcook/agent-skills/ralph-review)<a href="https://agentmods.dev/skills/zacharygcook/agent-skills/ralph-review"><img src="https://agentmods.dev/badge/skills/zacharygcook/agent-skills/ralph-review/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/zacharygcook/agent-skills/ralph-review"><img src="https://agentmods.dev/badge/skills/zacharygcook/agent-skills/ralph-review.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 | $0.00061 | $0.00296 |
| Opus 5.5 | $0.00024 | $0.00118 |
| Sonnet 5.5 | $0.00012 | $0.00059 |
| Haiku 4.5 | $0.00006 | $0.00030 |
Grade A, and why
ralph-review 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.
What it actually says
Ralph Review
Review the sprint as an evidence-backed delivery unit.
- Read repository instructions, the durable spec, sprint
README.md,IMPLEMENTATION_PLAN.md,relevant-specs.md,chunks.json, andSCRATCHPAD.md. - Inspect the actual commit range and changed artifacts. Do not accept summaries as proof.
- Verify every passed chunk against its acceptance criteria, validation logs, and commit evidence.
- Check final review, documentation, sprint-validation, and optional E2E hook states. Distinguish skipped, failed, interrupted, and completed hooks.
- Look for missing spec behavior, accidental scope, weak tests, stale documentation, unsafe orchestration state, and negative knowledge the next sprint must preserve.
- Report findings by severity, then give a clear verdict: complete, repairable before acceptance, or blocked. Name the exact evidence and next action.
Do not rewrite chunk state, manufacture evidence, or implement findings during a review-only request.
When installed beside $ralph-loop, consult references/review.md for the full shared rubric.
What ships with it
2 files 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.
- 1mo ago First seen · 23 lines · 61 tokens per session scan A 98ae2e55f20d
ralph-review is a skill published in the GitHub repository zacharygcook/agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 61 tokens to every session and 296 once invoked, about $0.0002 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 skills, from other repositories
code-refiner
Deep code simplification and refactoring preserving behavior across Python, Go, TypeScript, Rust. Targets complexity, anti-patterns, readability debt. Triggers on: "simplify this code", "refactor for clarity", "reduce complexity", "make this more readable", "tech debt cleanup", "too much nesting". NOT for deepening…
package-optimizer
Evaluate one existing package or bounded package family from recorded evaluator evidence and a capability profile, then propose retain, simplify, strengthen, retire, or inconclusive without editing. Use when optimizing a skill, agent, hook, rule, command, utility, or preset; evaluating whether package detail is…
concord-relay
Keep this Grok session reachable by other Concord agents while idle.
review-skill
Review a proposed Agent Skill for structural validity and content quality before publishing. Runs the skill-validator CLI to check for structural issues, scores the skill with an LLM judge, and interprets results to advise authors on what to address. Use when a user wants to review, validate, or quality-check an Agent…
plan-review
Pre-implementation plan audit stress-testing scope, assumptions, risks, and failure modes before code is written. Triggers on: "review this plan", "is this plan solid", "what am I missing", "challenge my assumptions", "stress-test this", "/plan-review".
pre-landing-review
Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage. Triggers on: "is this safe to land", "pre-landing review", "safety check before merge", "gate check", "/pre-landing-review". NOT for diff review, use pr-review.