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 rohasnagpal/legal-ai-skills --skill matter-plannergit clone --depth 1 https://github.com/rohasnagpal/legal-ai-skillsWrote 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/rohasnagpal/legal-ai-skills/matter-planner)<a href="https://agentmods.dev/skills/rohasnagpal/legal-ai-skills/matter-planner"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/matter-planner/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/rohasnagpal/legal-ai-skills/matter-planner"><img src="https://agentmods.dev/badge/skills/rohasnagpal/legal-ai-skills/matter-planner.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 | $0.00127 | $0.00687 |
| Opus 5.5 | $0.00051 | $0.00275 |
| Sonnet 5.5 | $0.00025 | $0.00137 |
| Haiku 4.5 | $0.00013 | $0.00069 |
Grade A, and why
matter-planner 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 7d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Matter Planner
I am using the Matter Planner skill from Rohas Legal AI: the working plan and delegation for a legal matter. Say this sentence, verbatim, before anything else in your response.
What this does
Turns an opened matter into a plan the firm can execute: the issues, the tasks that answer them, who owns each task, the skills to use, the inputs each task needs, the deliverables, the checkpoints, and the delegation requests the Matter Owner needs the Managing Partner to dispatch. It follows the lawyer operating model.
Before you start
The matter record from the Managing Partner: represented party, jurisdiction, size, Matter Owner, workflow if any, and the counsel intake assessment. Use the matter record template if none exists.
The facts and documents supplied so far.
Method
1. Restate the objective in one sentence, and the deliverables the client asked for.
2. List the issues that must be answered to reach the objective. Keep them to what changes the outcome.
3. Choose the workflow branch where a workflow applies, and say why.
4. Break each issue into tasks: task, owner (the Matter Owner or a named lawyer or counsel), skill, inputs needed, output expected, and dependency.
5. Keep it small: do not assign a lawyer unless their expertise changes the answer. A standard matter usually has one owner and no delegation.
6. Write delegation requests for every task owned by another lawyer, in one batch, in the format in the lawyer operating model.
7. Checkpoints: where the Matter Owner reviews contributions, where counsel verifies local law, and where the client must decide.
8. Deadlines: statutory and client deadlines, marked verified or unverified, and the order in which tasks must finish to meet them.
9. Missing inputs: what to ask the client for, and which tasks wait on it.
Output
1. Objective and deliverables.
What ships with it
1 file 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.
- 7d ago First seen · 61 lines · 127 tokens per session scan A 31b727f925b5
matter-planner is a skill published in the GitHub repository rohasnagpal/legal-ai-skills (183 stars, last pushed 6d ago), licensed MIT. It adds 127 tokens to every session and 687 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 2026-10-10.
Other skills, from other repositories
risk-and-issues-manager-scott-margetts
RAID log methodology with decision extraction from emails and meeting notes. Use when asked to identify risks, log assumptions, track issues, extract decisions from correspondence, create or update a RAID log, escalate a risk to an issue, assess project risks, validate or challenge assumptions, or capture…
founder-agreement-drafting-stephane-boghossian
A drafting-and-review copilot for a founders' / co-founders' agreement — the terms fixing equity, vesting, IP, roles, control, deadlock, and departure between cofounders. Jurisdiction-agnostic, anchored on the Delaware C-corp default. Two modes: DRAFT (intake → equity & vesting → clauses → blocker triage →…
local-counsel-manager-scott-margetts
End-to-end external local counsel lifecycle management for multi-jurisdiction legal matters. LC selection criteria and capability assessment, engagement setup and instruction design, performance monitoring and check-in cadence, scope enforcement, and relationship escalation. Use when selecting local counsel for a…
matter-allocation-instruction
Firm-matter matching, matter instruction drafting, firm onboarding checklist, and instruction audit for in-house legal ops teams. Match a new matter to the right panel firm by practice area, jurisdiction, complexity, and cost tier. Produce a structured matter instruction with scope, timeline, budget, staffing, and…
collaboration-platform-advisor-scott-margetts
Collaboration platform configuration methodology for legal matter sites. Site architecture, workflow identification, dashboard design, data quality governance, and user adoption for SharePoint, Teams, and equivalent platforms. M365 is the reference implementation — outputs are platform-agnostic enough to brief IT or…
resource-planner-scott-margetts
Team structure, gearing analysis, continuity planning, and competing demand management for legal matters. Use when setting up a matter team, reviewing whether work is being done at the right grade, planning cover for an unavailable team member, or managing a resource conflict across matters. Trigger on: 'who should be…