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 skills/code-yeongyu/lazyclaudecode/review-worknpx skills add code-yeongyu/lazyclaudecode --skill review-workgit clone --depth 1 https://github.com/code-yeongyu/lazyclaudecodeWrote 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/code-yeongyu/lazyclaudecode/review-work)<a href="https://agentmods.dev/skills/code-yeongyu/lazyclaudecode/review-work"><img src="https://agentmods.dev/badge/skills/code-yeongyu/lazyclaudecode/review-work.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 | $0.00116 | $0.05293 |
| Opus 5 | $0.00058 | $0.02646 |
| Sonnet 5 | $0.00023 | $0.01059 |
| Haiku 4.5 | $0.00012 | $0.00529 |
Grade A, and why
review-work scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Backend API**: Use curl/httpie to hit endpoints with various payloads, verify response codes and bodies. How it starts
The opening of the file, as written. The whole thing — 547 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Code Harness Tool Compatibility
This skill may include examples copied from the OpenCode or Codex harness. In Claude Code, do not call OpenCode/Codex-only tools such as task(...), call_omo_agent(...), spawn_agent(...), background_output(...), wait_agent(...), team_*(...), send_message(...), followup_task(...), or close_agent(...) literally. Translate those examples to Claude Code native tools:
| OpenCode / Codex example | Claude Code tool to use |
|---|---|
task(subagent_type="explore", ...) / call_omo_agent(...) / spawn_agent(agent_type="explorer", ...) |
the Task tool (spawn a subagent of the matching type) |
task(subagent_type="plan"/"oracle", ...) / spawn_agent(agent_type="plan"/"reviewer", ...) |
the Task tool with the planner/reviewer subagent, or the Skill tool |
task(category="...", ...) |
the Task tool (general-purpose subagent) or run the work inline |
background_output(...) / wait_agent(...) |
await the subagent's return value / the system completion notification |
team_*(...) / send_message/followup_task/close_agent |
run multiple Task subagents and synthesize their results |
When translating load_skills=[...], invoke the requested skills with the Skill tool or pass their names in the spawned subagent's prompt. If a code block below conflicts with this section, this section wins.
Review Work - 5-Agent Parallel Review Orchestrator
Launch 5 specialized sub-agents in parallel to review completed implementation work from every angle. All 5 must pass for the review to pass. If even ONE fails, the review fails.
The 5 agents cover complementary concerns - together they form a comprehensive review that no single reviewer could match:
| # | Agent | Type | Role | Focus Level |
|---|---|---|---|---|
| 1 | Goal Verifier | Oracle | Did we build what was asked? | MAIN |
| 2 | QA Executor | unspecified-high | Does it actually work? | MAIN |
| 3 | Code Reviewer | Oracle | Is the code well-written? | MAIN |
| 4 | Security Auditor | Oracle | Is it secure? | SUB |
| 5 | Context Miner | unspecified-high | Did we miss any context? | MAIN |
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.
- 5d ago First seen · 547 lines · 116 tokens per session scan A e43bca1cd3af
review-work is a skill published in the GitHub repository code-yeongyu/lazyclaudecode (18 stars, last pushed 3mo ago), licensed MIT. It adds 116 tokens to every session and 5,293 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
craft-style
Builds a personal output style on hush's frame — the user's voice on the surface, hush's silence-and-structure mechanics copied verbatim underneath. Manages its own creations: lists them alongside stock Hush and edits them. A mechanical verifier confirms every invariant survived. Activation is hush:pick-style's job …
checkpoint
Maintain a thirty-second return point (CHECKPOINT.md) and a single-use handoff (HANDOFF.md) so any session can resume mid-goal without archaeology. Use when a large unit of work finishes, a session enters its closing stretch, when leaving instructions for the next session, or when resuming and the user asks where…
verify-gate
Treat research results and model knowledge as drafts until verified. Use when researching, quoting numbers or sources, recording knowledge as fact, or before declaring a task successful.
goal
Run a large or unfamiliar goal through the full ballast pipeline — mobilize what you already hold, terrain scan, full skeleton, atomic foundation learning with verification, then build from bedrock to a verified done. Use when the user hands over a big goal, enters a new field, or asks to learn X in order to achieve Y.
brain-init
Scaffold a file-based memory system (index, decision ledger, open questions, session log, optional product truth file) so a project can serve as a durable second brain. Use when the user wants to set up memory, an external brain, or the ballast structure in a project.
proof-standard
Never make an external-facing claim about a product without evidence from a truth file. Use when writing marketing copy, announcements, docs, landing pages, investor material, or answering "can our product do X".