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.
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 modu-ai/moai-adk --skill hns-lsel-curatorgit 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/hns-lsel-curator)<a href="https://agentmods.dev/skills/modu-ai/moai-adk/hns-lsel-curator"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/hns-lsel-curator/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/hns-lsel-curator"><img src="https://agentmods.dev/badge/skills/modu-ai/moai-adk/hns-lsel-curator.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 Rogue Agent · line 205 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00135 | $0.05758 |
| Opus 5.5 | $0.00054 | $0.02303 |
| Sonnet 5.5 | $0.00027 | $0.01152 |
| Haiku 4.5 | $0.00014 | $0.00576 |
Grade A, and why
hns-lsel-curator 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 20d 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 — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hns-lsel-curator — LSEL CLUSTER + drain engine
Namespace:
hns-lsel-*is user-owned dogfood (CLAUDE.local.md §24). This skill is NOT mirrored intointernal/template/templates/— it lives only in this repo. Graduation tomoai-lsel-*+ 16-language distribution is a separate SPEC (out of scope per spec.md §G).M1 scope: drain + cluster + stage candidates. NO APPROVE, NO APPLY (M3). M2 scope: drain + cluster + PROPOSE shadow (no APPROVE, no APPLY). The PROPOSE stage emits shadow proposals + self-critiques; APPROVE/APPLY land in M3 via the fresh
hns-lsel-applierpath. M2 does NOT write tomemory/— the firstfeedback_*.mdtopic file is an M3+ deliverable after APPROVE.
What this skill does
The MoAI-ADK repo accumulates failure-event stubs in .moai/lessons-inbox.jsonl — a moving
target; the measured composition and its dated baseline live in the scope anchor document
(.moai/docs/learning-channel-scope.md), never in prose here. The constitution names the
orchestrator as the drain actor, but until this skill there was zero mechanical drain code —
the drain existed only as a doctrine paragraph (moai-constitution.md:147). This skill closes
that gap in user-owned surfaces, without touching the frozen Go applier
(internal/harness/applier.go:22 — its write-flag stays false; REQ-LSEL-003: bypass, never
unfreeze).
Channel scope (bounded claim): the inbox records failure-event stubs only — the two wired
families tool_failure:<tool>:<sig> and test_fail:<pkg>: (the test-fail family is wired via
the evidence writer's test-fail path; the writer itself is untouched here). It does not capture
defect families that produce neither a tool failure nor a test failure — those travel through
the human-mediated loop (lane discovery → lead judgment → auto-memory feedback_*.md +
MEMORY.md record), which is their learning channel. Numbers live only in the anchor document.
The drain is split into a mechanical core (drain.sh, deterministic, testable) and a
model-mediated layer (this SKILL.md + your judgment, invoked for M2+ importance refinement
and proposal drafting).
What ships with it
11 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.
- backlog_check_test.sh 4.0 KB runs code
- backlog_check.sh 3.6 KB runs code
- csa_refusal_test.sh 5.1 KB runs code
- drain_test.sh 9.3 KB runs code
- drain.sh 5.6 KB runs code
- propose_test.sh 3.2 KB runs code
- reflect_test.sh 5.9 KB runs code
- reflect.sh 4.8 KB runs code
- session_drain_test.sh 13 KB runs code
- session_drain.sh 7.5 KB runs code
- tier4_firing_test.sh 5.2 KB runs code
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.
- 20d ago Changed c2234a0d628c
- 22d ago Changed · +9 lines 25fb22d723a1
- 1mo ago First seen · 402 lines · 135 tokens per session scan A a2d1abd6ed9e
hns-lsel-curator is a skill published in the GitHub repository modu-ai/moai-adk (1,237 stars, last pushed yesterday), licensed Apache-2.0. It adds 135 tokens to every session and 5,758 once invoked, about $0.0005 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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