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 ThomasMoreAI/legal-skills-open --skill triage-government-ai-use-case-l0ckagit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote 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/thomasmoreai/legal-skills-open/triage-government-ai-use-case-l0cka)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/triage-government-ai-use-case-l0cka"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/triage-government-ai-use-case-l0cka/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/thomasmoreai/legal-skills-open/triage-government-ai-use-case-l0cka"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/triage-government-ai-use-case-l0cka.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00111 | $0.01110 |
| Opus 5.5 | $0.00044 | $0.00444 |
| Sonnet 5.5 | $0.00022 | $0.00222 |
| Haiku 4.5 | $0.00011 | $0.00111 |
Grade A, and why
triage-government-ai-use-case-l0cka 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 8d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Triage Government AI Use Case
Route the use case to the right jurisdictional assurance track and name the artefacts and escalation threshold that track requires. The triage output is a routing, not a completed assessment.
Read the source and control method and use the government AI assurance registry.
Workflow
- Fix the entity and use case.
- Record the agency, jurisdiction, the AI system or use case, its purpose, affected people and deployment status. For a Commonwealth entity, confirm whether it is a non-corporate entity covered by the mandatory DTA policy.
- Select the track from the registry.
- Match the jurisdiction to its registry entry. Re-verify the named
official source at use time: the registry is a research snapshot, and
entries marked
lead-verify-before-useorverified-with-caveat(SA and Tasmania at the snapshot date) must be confirmed against the official page or document before any assertion. - Note the national assurance framework as the cross-jurisdiction baseline, pegged to Australia's AI Ethics Principles.
- Match the jurisdiction to its registry entry. Re-verify the named
official source at use time: the registry is a research snapshot, and
entries marked
- Name the required artefacts and threshold.
- Commonwealth: accountable official, AI transparency statement and AI impact assessment under DTA policy v2.0, with its phased commencement checked at the assessment date (remaining requirements, including AI impact assessments, reportedly due by 15 December 2026 — verify).
- States and territories: the framework's self-assessment or risk assessment, and the escalation body or trigger recorded in the registry (for example NSW AI Review Committee; NT AI advisory service for medium and high-risk projects).
- Flag adjacent obligations without assessing them.
- Route privacy depth to
$assess-ai-privacy-cybersecurity-use-caseand jurisdictional privacy routing to$route-australian-privacy-jurisdiction. Verify any statutory proposition with the relevant$check-*-legislationskill. - Court or tribunal generative-AI practice directions are
OUTSIDE SCOPE— identify the court and stop.
- Route privacy depth to
- Set the human decision gate.
- Name the accountable role in the agency, the artefacts to complete and the unresolved questions the assurance process must answer.
What ships with it
3 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.
- 8d ago First seen · 103 lines · 111 tokens per session scan A 9525bd992af2
triage-government-ai-use-case-l0cka is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (89 stars, last pushed 4d ago), licensed Apache-2.0. It adds 111 tokens to every session and 1,110 once invoked, about $0.0004 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 2026-10-09.
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