MoAI-ADK is a Go-based harness that organizes and verifies Claude Code work across planning, implementation, synchronization, and review stages. Developers use it to structure agentic coding tasks, apply quality gates, and route work across language models, while the catalogue entries extend its workflow with skills, hooks, commands, MCP servers, instructions, and settings.
Borrowing it
Nothing to install: this file belongs to modu-ai/moai-adk. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/modu-ai/moai-adk/main/.claude/skills/moai-harness-learner/SKILL.mdgit clone --depth 1 https://github.com/modu-ai/moai-adkWrote 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/modu-ai/moai-adk/moai-harness-learner)<a href="https://agentmods.dev/skills/modu-ai/moai-adk/moai-harness-learner"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-harness-learner/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/modu-ai/moai-adk/moai-harness-learner"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-harness-learner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 143 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.01766 |
| Opus 5 | $0.00030 | $0.00883 |
| Sonnet 5 | $0.00012 | $0.00353 |
| Haiku 4.5 | $0.00006 | $0.00177 |
Grade A, and why
moai-harness-learner 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 10d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
moai-harness-learner
Coordinator skill for the Harness Learning Subsystem (the harness-learning policy, superseded by the harness foundation policy as the active V3R4 foundation; this V3R3 SPEC's 4-tier ladder is preserved unchanged).
Produces Tier 4 auto-update proposal payloads consumed by the MoAI orchestrator; the orchestrator surfaces them to the user via AskUserQuestion and orchestrates Apply/Rollback flows. Canonical contract: .claude/rules/moai/core/askuser-protocol.md § Orchestrator-Subagent Boundary (the constitutional rule/002/003).
Quick Reference
Role: Orchestrator-side bridge between CLI (moai harness) and AskUserQuestion.
Key constraint [HARD]: moai harness apply returns a JSON payload representing a Tier 4 auto-update proposal. This skill produces the payload; the orchestrator surfaces it via AskUserQuestion. The CLI itself does NOT prompt the user. Canonical contract: .claude/rules/moai/core/askuser-protocol.md § Orchestrator-Subagent Boundary.
Common triggers:
moai harness status— check tier distribution and pending proposalsmoai harness apply— load next pending proposal (returns JSON payload)moai harness rollback <date>— restore snapshotmoai harness disable— set learning.enabled: false
Workflow:
- Run
moai harness statusto inspect state. - Run
moai harness applyto get the proposal payload. - Hand payload to the orchestrator for
AskUserQuestionsurfacing (approve / reject). - On approve: write approval to proposals dir and signal CLI to proceed.
- On reject: remove proposal file (no changes applied).
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.
- 10d ago First seen · 144 lines · 61 tokens per session scan A 74cf8664d908
moai-harness-learner is a skill published in the GitHub repository modu-ai/moai-adk (1,204 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 1,766 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 skills, from other repositories
code-reviewer
Automatic code quality and best practices analysis. Use proactively when files are modified, saved, or committed. Analyzes code style, patterns, potential bugs, and security basics. Triggers on file changes, git diff, code edits, quality mentions.
test-generator
Automatically suggest tests for new functions and components. Use when new code is written, functions added, or user mentions testing. Creates test scaffolding with Jest, Vitest, Pytest patterns. Triggers on new functions, components, test requests, testing mentions.
api-documenter
Auto-generate API documentation from code and comments. Use when API endpoints change, or user mentions API docs. Creates OpenAPI/Swagger specs from code. Triggers on API file changes, documentation requests, endpoint additions.
readme-updater
Keep README files current with project changes. Use when project structure changes, features added, or setup instructions modified. Suggests README updates based on code changes. Triggers on significant project changes, new features, dependency changes.
security-auditor
Continuous security vulnerability scanning for OWASP Top 10, common vulnerabilities, and insecure patterns. Use when reviewing code, before deployments, or on file changes. Scans for SQL injection, XSS, secrets exposure, auth issues. Triggers on file changes, security mentions, deployment prep.
version-check
Recommend which Claude Code version to run, or whether to update. Use when asked which Claude Code version is best/safe, whether to update now, whether a recent release is buggy, or what changed since the installed version.