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 map-tribunal-review-deadlines-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/map-tribunal-review-deadlines-l0cka)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/map-tribunal-review-deadlines-l0cka"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/map-tribunal-review-deadlines-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/map-tribunal-review-deadlines-l0cka"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/map-tribunal-review-deadlines-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 | $0.00141 | $0.01049 |
| Opus 5.5 | $0.00056 | $0.00420 |
| Sonnet 5.5 | $0.00028 | $0.00210 |
| Haiku 4.5 | $0.00014 | $0.00105 |
Grade A, and why
map-tribunal-review-deadlines-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 19d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Map Tribunal Review Deadlines
Map candidate review deadlines from the tribunal computation-rule tables and compute only through the bundled script. The enabling enactment frequently fixes its own period — the general tribunal layer is a candidate, never a conclusion.
Read the source and control method, use an approved profile per the deadline profile schema, and run compute_deadline.py against the computation-rule tables.
Workflow
- Fix the decision and the inputs.
- Record the decision, the decision-maker, the tribunal, and the
lawyer-supplied notification date as an assumption. A contested or
unknown notification date is
NOT READY.
- Record the decision, the decision-maker, the tribunal, and the
lawyer-supplied notification date as an assumption. A contested or
unknown notification date is
- Locate every candidate period.
- Take the general tribunal-layer candidate from the tribunal's table
(
art,ncat,qcat), and flag that the Act conferring the decision may fix a different period (for QCAT, s 6(7) of the QCAT Act says so expressly). Verify the conferring Act through$check-commonwealth-legislationor the applicable state checker. - For VCAT no general default period exists — the enabling enactment
always fixes the period (see the
vcattable note); identify the conferring provision and route its verification before any candidate is stated. - For tribunals without a table, produce identify-only output naming the enabling Act.
- Take the general tribunal-layer candidate from the tribunal's table
(
- Compute through the script only.
- Run the script per candidate. Report
computedandidentify_onlyresults faithfully, with every warning. - For any migration matter, always include the warning that migration time limits are non-extendable or jurisdictional and have changed repeatedly, and flag specialist review before reliance. Never conclude that a migration period has expired or that an extension is available.
- Run the script per candidate. Report
- Set the human decision gate.
- Name the confirmer who must confirm each candidate, resolve the conferring-Act period and enter dates in the diary system of record.
What ships with it
2 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.
- 19d ago First seen · 96 lines · 141 tokens per session scan A 9ef9037e7e4f
map-tribunal-review-deadlines-l0cka is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 141 tokens to every session and 1,049 once invoked, about $0.0006 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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