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 sergeyklay/.agents --skill review-implgit clone --depth 1 https://github.com/sergeyklay/.agentsWrote 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/sergeyklay/.agents/review-impl)<a href="https://agentmods.dev/skills/sergeyklay/.agents/review-impl"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/review-impl/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/sergeyklay/.agents/review-impl"><img src="https://agentmods.dev/badge/skills/sergeyklay/.agents/review-impl.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 | $0.00155 | $0.01721 |
| Opus 5.5 | $0.00062 | $0.00688 |
| Sonnet 5.5 | $0.00031 | $0.00344 |
| Haiku 4.5 | $0.00015 | $0.00172 |
Grade A, and why
review-impl 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Review
Task
What was implemented: Provided by the user as a task description or task tracker reference.
Process
Step 1: Resolve Task Reference
- If the invoker has already quoted the issue title and body in this prompt (typical when an orchestrator fetched the tracker in an earlier phase and passed the context forward), use those values as the canonical task description for all subsequent steps and do not re-fetch.
- Otherwise, if the task description above contains a GitHub issue URL (e.g.
https://github.com/owner/repo/issues/123) or a shorthand reference (e.g.owner/repo#123or#123), rungh issue view <url-or-reference> --json title,bodyto fetch the issue title and body. Use the fetched title and body as the canonical task description for all subsequent steps. - Otherwise, if the task description above contains a Jira issue URL (e.g.
https://yourcompany.atlassian.net/browse/PROJ-123), use appropriate Agent Skills and/or MCP tools to fetch the issue summary and description, and use those as the canonical task description for all subsequent steps. - If the task description is plain text and no issue context was provided, skip this step.
Step 2: Understand the Project
Before evaluating any changes, build a mental model of the system:
- Read project context files:
AGENTS.md,README.md,CONTRIBUTING.md, and anything indocs/. - List the project root and key subdirectories to understand module structure and layering.
- Read build/dependency manifests to understand the tech stack.
- Search for code review standards or guidelines the project defines.
Step 3: Understand the Task
Analyze the task description to determine:
- What problem is being solved or what capability is being added?
- Which architectural layers and modules should be affected?
- What quality attributes matter most for this change (correctness, performance, security, maintainability)?
Step 4: Discover What Changed
Identify the implementation changes using all available signals:
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 Changed 0be7b1877154
- 1mo ago Changed fb6963e500f5
- 1mo ago Changed · +17 lines 947a884ba6f0
- 1mo ago First seen · 120 lines · 155 tokens per session scan A 29a56c277316
review-impl is a skill published in the GitHub repository sergeyklay/.agents (6 stars, last pushed 4d ago), licensed Apache-2.0. It adds 155 tokens to every session and 1,721 once invoked, about $0.0006 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
audit
Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.
review
Review Elixir/Phoenix changes before committing — bugs, security, Ecto, LiveView, and Oban anti-patterns, via parallel specialist agents. Use when asked to review changes, a component, a diff, or a PR.
phx-pr-review
Address feedback left on a GitHub pull request: fetch unresolved review threads, make agreed Elixir/Phoenix code fixes, reply, and resolve. Use for a PR URL/number or reviewer comments. NOT for pre-PR review, findings triage, or CI monitoring.
boundaries
Analyze Phoenix context boundaries and module coupling via mix xref. Use when checking cross-context calls, validating dependencies, before splitting modules, or reviewing architecture.
challenge
Challenge mode reviews - rigorous questioning before approving changes. Use when you want thorough scrutiny of Ecto changes, LiveView events, OTP designs, or PR readiness.
codex-ab
Run an A/B codex review experiment — holistic codex review vs 3 focused dimension passes (security, ecto, liveview) on the branch diff, classify findings, report a panel-value verdict. Use when the branch is fresh, before any codex review runs.