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Official agent skill

Cold Call Prep

by anthropics in anthropics/claude-for-legal

Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class.

OfficialApache-2.0Auto-check passedSales & Support

Install Cold Call Prep

skills CLI
$ npx skills add anthropics/claude-for-legal --skill cold-call-prep -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install anthropics/claude-for-legal cold-call-prep --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/anthropics/claude-for-legal.git skills-src && mkdir -p .claude/skills && cp -r skills-src/law-student/skills/cold-call-prep .claude/skills/cold-call-prep && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cold-call-prep
GitHub stars
9.6k
Used in
3 other repos
Token cost
~1.8k tokens
SKILL.md length
892 words
Files
1
Skills in repo
147
Repo updated
First seen
Licence
Apache-2.0

At a glance

Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class.

  • Works in 4 steps: Identify the reading + professor → Predict the questions → Drill → …
  • The user says prep for class tomorrow
  • SKILL.md covers Real-matter check, Purpose, Confidence discipline and Load context, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Cold Call Prep is an agent skill from anthropics/claude-for-legal, published by the product's own GitHub organization. Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class. Use when the user says "prep for class tomorrow", "cold call [case]", "what might [professor] ask on", or points at assigned reading.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Sales call preparation. The repository describes itself as: A suite of plugins for legal workflows. The licence is Apache-2.0.

When your agent uses it

  • The user says prep for class tomorrow
  • Cold call [case]
  • What might [professor] ask on
  • Points at assigned reading

Example prompts

  • “s likely questions and drill them Socratically, flagging where you”
  • “prep for class tomorrow”
  • “cold call [case]”
  • “/cold-call-prep”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Identify the reading + professor
  2. Predict the questions
  3. Drill
  4. Post-drill summary

What it can do on your machine

Read from SKILL.md and the folder at commit 4a6c651. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cold Call Prep loads about 1.8k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 892 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from anthropics/claude-for-legal at commit 4a6c651, republished under its Apache-2.0 licence (© anthropics). 892 words, ~1,794 tokens.

Download SKILL.mdSave it as .claude/skills/cold-call-prep/SKILL.md (or your agent's skills folder).
name
cold-call-prep
description
Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class. Use when the user says "prep for class tomorrow", "cold call [case]", "what might [professor] ask on", or points at assigned reading.
argument-hint
[case name, or paste case text, or path to reading]

/cold-call-prep

  1. Load ~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md → class list, professors, learning style.
  2. Apply the workflow below.
  3. Identify reading (case name + citation, professor, class, syllabus context).
  4. Predict 6-10 likely questions across categories (Facts / Holding / Reasoning / Application / Policy), weighted to professor's known tendencies.
  5. Drill using socratic pattern — ask, wait, push back, narrow when stuck. Don't give answers.
  6. 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 dollar 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 lawyer yet. If this is real, [the person] needs an actual lawyer: legal aid, your school's clinic, a lawyer referral service (your jurisdiction's bar association, law society, or legal aid body), or (if there's money) a private attorney. 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 dollar amounts, "my landlord/boss/parent/friend," "I got a ticket/letter/notice," deadlines measured in days. Any one of these is a trigger.

Purpose

Cold-calling lives or dies on preparation. The professor 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."

Load context

  • ~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md → current classes, professors, learning style
  • User-provided: case name / case text / casebook pages / reading list

Workflow

Step 1: Identify the reading + professor
  • Case name and citation
  • Professor (from ~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md class list — tone and focus vary by professor)
  • Class / subject area
  • Where this case falls in the syllabus (for context — is this the first case on the topic, a narrowing case, a counterexample?)
Show full SKILL.md (455 more words)Show less
Step 2: Predict the questions

Professors cold-call in recurring patterns. Predict across these categories:

Facts-level (warm-up):

  • Who are the parties? What happened? Procedural posture?
  • What did the trial court do? The appellate court below?
  • Why is this in the casebook? What subject is it illustrating?

Holding / rule:

  • What's the holding? One sentence.
  • What's the rule that comes out of this case — the portable takeaway?
  • How would you phrase the rule if it were in your outline?

Reasoning:

  • Why did the court decide this way?
  • What arguments did the court reject?
  • Was there a dissent? What did it argue?

Application / hypos:

  • What if [fact X] were different — same outcome?
  • How does this case compare to [prior case in the syllabus]?
  • What's the limiting principle? Where does this rule stop?

Policy / theory:

  • What's the policy the court is protecting?
  • Does this rule make sense? Alternative approaches?

Professor-specific flavor (from ~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md notes):

  • If the professor is known for hypo-heavy calls, weight Application/Hypo questions
  • If policy-heavy, weight Policy/Theory
  • If fact-heavy socratic (Socratic 101 Paper Chase style), weight Facts + Holding

Pick 6-10 questions across these categories. Rank by likelihood of being asked first (Facts usually go first, then Holding, then the harder categories).

Step 3: Drill

Use the socratic-drill pattern:

  1. Ask Question 1. Wait for answer.
  2. If right + well-reasoned: acknowledge, move to Question 2.
  3. If right but sloppy: don't let it slide. "You got there, but explain — why does the court's reasoning support that?"
  4. If wrong: don't give the answer. Ask a narrowing question. "What facts does the court rely on?" Walk them to it.
  5. If stuck: narrow further. "Before we go to the holding — what's the procedural posture?"
  6. If genuinely lost: tell them to re-read the case. "This is a re-read, not a guess-your-way-through. Come back when you've read it again."
Step 4: Post-drill summary

At the end:

markdown
# Cold-Call Prep — [case] — [date]

**Questions drilled:** [N]
**Strong:** [questions where they were confident + right]
**Shaky:** [questions where they guessed or hedged]
**Missed:** [questions where they didn't know]

## Before class tomorrow:
- [specific thing to re-check — facts they got wrong, rule they couldn't state]
- [if shaky on policy/theory: "read the dissent again — that's usually where policy questions come from"]

## Questions likely to come up in class:
- [top 3 of the 10 — the ones the professor is most likely to lead with]

Integration

  • case-brief: if the student hasn't briefed the case yet, offer to run /law-student:case-brief before cold-call prep. A brief is a cold-call prep tool too.
  • socratic-drill: if prep surfaces a weak spot in the subject (not just this case), follow with /law-student:socratic-drill [subject].
  • flashcards: if the case's rule is one the student should memorize, offer to add to the flashcard deck.

What this skill does not do

  • Be the professor. The actual cold-call can go anywhere. This skill predicts patterns; professors surprise.
  • Replace reading the case. If you haven't read it, the skill can't help you — questions require text you've absorbed.
  • Give you the case's holding without asking you first. Drill-me pattern: I ask, you answer.
  • Predict jurisdiction-specific niche questions. If the professor has known hobby horses, capture them in ~/.claude/plugins/config/claude-for-legal/law-student/CLAUDE.md class notes and the skill can weight accordingly; otherwise, it works from general patterns.

© anthropics, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in law-student/skills/cold-call-prep of anthropics/claude-for-legal.

Open the folder on GitHubat commit 4a6c651

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in anthropics/claude-for-legal, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Cold Call Prep next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cold Call Prep compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cold Call Prep this skillanthropics/claude-for-legal9.6k3 repos~1.8kAutomated safety check: PassApache-2.0
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Luopan Company Researchzhangxiaoqiang1991/luopan388—~998Automated safety check: PassMIT
Company Researchstophobia/deerflow2.0-enhanced820—~845Automated safety check: PassMIT
Enterprise Customer Visit Playbookzj-unicom-ai/UniEmployee358—~458Automated safety check: PassMIT
SdtStopDisTrain/sdt-skills309—~535Automated safety check: PassMIT

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Categories

Questions about Cold Call Prep

What does Cold Call Prep do?

Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class. Cold Call Prep is an agent skill from anthropics/claude-for-legal, published by the product's own GitHub organization. Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class.

When should I use Cold Call Prep?

Cold Call Prep fits situations like: the user says prep for class tomorrow; cold call [case]; what might [professor] ask on; points at assigned reading.

How do I install Cold Call Prep in Claude Code?

Run `npx skills add anthropics/claude-for-legal --skill cold-call-prep -a claude-code`. Or copy the skill folder (law-student/skills/cold-call-prep in anthropics/claude-for-legal) into .claude/skills/cold-call-prep in your project. Claude Code loads it when a task matches its description.

How do I install Cold Call Prep in Codex?

Run `npx skills add anthropics/claude-for-legal --skill cold-call-prep -a codex`. Or copy the skill folder (law-student/skills/cold-call-prep in anthropics/claude-for-legal) into .agents/skills/cold-call-prep in your project. Codex loads it when a task matches its description.

Can I use Cold Call Prep in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add anthropics/claude-for-legal --skill cold-call-prep -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cold-call-prep, .gemini/skills/cold-call-prep, .github/skills/cold-call-prep and .opencode/skills/cold-call-prep in your project.

What does Cold Call Prep need to run?

SKILL.md names no scripts, command-line tools or credentials: Cold Call Prep is instructions for the agent only.

Does Cold Call Prep access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Cold Call Prep safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cold Call Prep use?

Cold Call Prep is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cold Call Prep use?

About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cold Call Prep?

Skills that share tags, products or a category with Cold Call Prep: Meeting Prep Brief (BrianRWagner/ai-marketing-claude-code-skills, 440 stars), Luopan Company Research (zhangxiaoqiang1991/luopan, 388 stars), Company Research (stophobia/deerflow2.0-enhanced, 820 stars) and Enterprise Customer Visit Playbook (zj-unicom-ai/UniEmployee, 358 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cold Call Prep?

anthropics (a GitHub organization, an official publisher) maintains it in anthropics/claude-for-legal, which has 9,617 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on September 29, 2026.

Source: anthropics/claude-for-legal on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.