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 uk-agents/uk-legal-plugins --skill cold-call-prepgit clone --depth 1 https://github.com/uk-agents/uk-legal-pluginsWrote 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/uk-agents/uk-legal-plugins/cold-call-prep)<a href="https://agentmods.dev/skills/uk-agents/uk-legal-plugins/cold-call-prep"><img src="https://agentmods.dev/badge/skills/uk-agents/uk-legal-plugins/cold-call-prep/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/uk-agents/uk-legal-plugins/cold-call-prep"><img src="https://agentmods.dev/badge/skills/uk-agents/uk-legal-plugins/cold-call-prep.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 | $0.00074 | $0.01815 |
| Opus 5 | $0.00037 | $0.00907 |
| Sonnet 5 | $0.00015 | $0.00363 |
| Haiku 4.5 | $0.00007 | $0.00181 |
Grade A, and why
cold-call-prep 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/law-student-uk:cold-call-prep
- Load
~/.claude/plugins/config/uk-legal-plugins/law-student-uk/CLAUDE.md→ module list, lecturers, learning style. - Apply the workflow below.
- Identify reading (case name + OSCOLA citation, lecturer, module, syllabus context).
- Predict 6-10 likely questions across categories (Facts / Holding / Reasoning / Application / Policy), weighted to lecturer's known tendencies.
- Drill using Socratic pattern — ask, wait, push back, narrow when stuck. Don't give answers.
- Post-drill summary: strong/shaky/missed; what to re-check before class.
Real-matter check
If the question the student is asking sounds like it's about a REAL situation — their lease, their parking ticket, their family's business, their friend's arrest, a real pound amount, a real deadline, a real party name — stop.
"This sounds like a real situation, not a hypothetical. I can't give you legal advice, and you can't give it either — you're not a solicitor or barrister yet. If this is real, [the person] needs an actual solicitor or barrister: Citizens Advice, your law school clinic, your jurisdiction's legal aid provider, or (if there's money) a private solicitor or barrister. I'm happy to help you understand the general legal concepts involved, but that's study, not advice."
Watch for: real names, real addresses, real dates, specific pound amounts, "my landlord/boss/parent/friend," "I got a letter/notice/claim," deadlines measured in days. Any one of these is a trigger.
Purpose
Cold-calling in UK law seminars lives or dies on preparation. The seminar leader has read the case dozens of times and knows the questions; the student has read it once. This skill narrows the gap — predicts the likely question patterns for the case, drills the student on them, and surfaces what they haven't locked in.
Not a replacement for reading the case. A test that you actually did.
Confidence discipline
- When the student provides case text or casebook excerpts: I predict questions based on the actual text. Confident.
- When the student provides only a case name: I predict based on what I know about the case. Flag
[UNCERTAIN]on any question that depends on case details I'm not sure of. Strongly recommend the student pastes the case or casebook treatment first. - If I don't know the case well: say so. "I don't have a reliable read on this case — paste the text or casebook treatment and I can work from that. Otherwise my questions are educated guesses."
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 · 139 lines · 74 tokens per session scan A 37d3e0b5351a
cold-call-prep is a skill published in the GitHub repository uk-agents/uk-legal-plugins (9 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 74 tokens to every session and 1,815 once invoked, about $0.0004 per session on Opus 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 2026-09-03.
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