moai-harness-learner

moai-harness-learner is a skill for Claude Code from modu-ai/moai-adk. It costs 61 tokens per session (1,827 once invoked), scanned A, original, Apache-2.0.

A coordinator for a system that learns from how a coding-agent workflow is used and prepares proposed policy updates. It also handles applying or rolling back those proposals through the surrounding orchestrator.

In plain words
What is it for?
Use it to check learning status, retrieve pending update proposals, and coordinate applying or rolling back harness-learning changes.
Why use it?
It provides a controlled way to review and manage automatically suggested changes instead of changing the workflow policy directly.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: reads .claude/ paths; mentions subagents; names the AskUserQuestion tool.

Good fit Use it to check learning status, retrieve pending update proposals, and coordinate applying or rolling back harness-learning changes.

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Install with agentmods
npx agentmods add skills/modu-ai/moai-adk/moai-harness-learner
About the project

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.

modu-ai/moai-adk · 1,236 stars · on GitHub · adk.mo.ai.kr

Install

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.

Any agent
npx skills add modu-ai/moai-adk --skill moai-harness-learner
Clone the repo
git clone --depth 1 https://github.com/modu-ai/moai-adk

Made for: Claude Code.

Wrote 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.

agentmods badge for moai-harness-learner

README.md
[![agentmods](https://agentmods.dev/badge/skills/modu-ai/moai-adk/moai-harness-learner/github.svg)](https://agentmods.dev/skills/modu-ai/moai-adk/moai-harness-learner)
Your own site
<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.

agentmods 80×15 button for moai-harness-learner

Your own site · 80×15
<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>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,827 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.01827
Opus 5.5 $0.00024 $0.00731
Sonnet 5.5 $0.00012 $0.00365
Haiku 4.5 $0.00006 $0.00183

Measured 17d ago against content hash 1817ae807f6b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 17d 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.

.claude/skills/moai-harness-learner/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 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 foundation policy is the active contract; the 4-tier ladder from the earlier harness-learning policy 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.

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 proposals
  • moai harness apply — load next pending proposal (returns JSON payload)
  • moai harness rollback <date> — restore snapshot
  • moai harness disable — set learning.enabled: false

Workflow:

  1. Run moai harness status to inspect state.
  2. Run moai harness apply to get the proposal payload.
  3. Hand payload to the orchestrator for AskUserQuestion surfacing (approve / reject).
  4. On approve: write approval to proposals dir and signal CLI to proceed.
  5. On reject: remove proposal file (no changes applied).

Read the full file on GitHub · 150 lines

Changes

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.

  1. 17d ago Changed 1817ae807f6b
  2. 19d ago Changed · +6 lines 3d106b3c43ed
  3. 1mo ago First seen · 144 lines · 61 tokens per session scan A 74cf8664d908

Subscribe to this mod's changes

moai-harness-learner is a skill published in the GitHub repository modu-ai/moai-adk (1,236 stars, last pushed today), licensed Apache-2.0. It adds 61 tokens to every session and 1,827 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 2026-08-30.

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