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 Makisuo/skills --skill effect-reviewgit clone --depth 1 https://github.com/Makisuo/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/makisuo/skills/effect-review)<a href="https://agentmods.dev/skills/makisuo/skills/effect-review"><img src="https://agentmods.dev/badge/skills/makisuo/skills/effect-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/makisuo/skills/effect-review"><img src="https://agentmods.dev/badge/skills/makisuo/skills/effect-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00071 | $0.01246 |
| Opus 5.5 | $0.00028 | $0.00498 |
| Sonnet 5.5 | $0.00014 | $0.00249 |
| Haiku 4.5 | $0.00007 | $0.00125 |
Grade A, and why
effect-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.
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.
Effect-TS Code Review
Orchestrate a multi-agent review of code changes against Effect-TS best practices.
Workflow
Step 1: Discover Changed Files
Run git diff --name-only main...HEAD to find all changed files on the current branch. If that fails (e.g., on main), fall back to git diff --name-only HEAD~1 or git diff --name-only for unstaged changes.
List the changed files for the user.
Step 2: Categorize Files
Split files into categories:
- Backend Effect files:
.tsfiles NOT ending in.test.ts, NOT config files (.config.ts,tsconfig, etc.), NOT UI component library directories - Test files:
.test.tsfiles - UI files:
.tsxfiles - Skip:
.md,.json,.yml,.css, config files, generated files
Step 3: Launch Sub-Agents in Parallel
Based on which categories have files, launch the appropriate agents using the Agent tool. Launch all applicable agents in a single message for maximum parallelism.
If backend Effect files exist, launch these 4 agents in parallel:
effect-primitives-reviewer— checks Effect primitives (Array, Match, Option, forEach, no try/catch, no async/await, Layer not Effect.provide)branded-types-reviewer— checks branded type usage for all entity IDsotel-reviewer— checks tracing setup (Effect.fn trace names, annotateCurrentSpan, structured logging)error-reviewer— checks error definitions and handling (Schema.TaggedError, catchTag, rich context)typescript-reviewer— checks TypeScript patterns (noas any, prefersatisfiesoveras, no manual type annotations on inferred types)
If test files exist, launch:
test-coverage-reviewer— checks @effect/vitest patterns and assesses coverage gaps
If UI files exist, launch:
ui-reviewer— checks component library usage, accessibility, layout, brand consistency
For each agent, provide the prompt:
Review the following files for [agent's specialty]. Read each file and produce a structured report with Critical/Warning/Info findings.
Files to review:
- [list of file paths]
Also review the reference guide at
references/[relevant-reference].md(relative to this skill) for the detailed checklist.
What ships with it
7 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 · 137 lines · 71 tokens per session scan A b31f5dfee34a
effect-review is a skill published in the GitHub repository Makisuo/skills (79 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 1,246 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
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Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
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revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…