A guided command for practising interview questions and receiving coaching on answers. It supports question types such as behavioral, technical, coding, system design, case, and recruiter-screen questions.

Use it to generate a small set of practice questions and work through answers one at a time with coaching.

It gives interview practice matched to the job role, question type, and difficulty instead of offering unrelated questions.

practice — Command by fourleafai

Install

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.

agentmods

npx agentmods add commands/fourleafai/clover-public/practice

Clone the repo

git clone --depth 1 https://github.com/fourleafai/clover-public

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 606 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00000	$0.00606
Opus 5	$0.00000	$0.00303
Sonnet 5	$0.00000	$0.00121
Haiku 4.5	$0.00000	$0.00061

Measured 2d ago against content hash 56251fcd132c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

practice 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 2d 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.

skills/four-leaf-coach/references/commands/practice.md · 50 lines

How it starts

The opening of the file, as written. The whole thing — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.

practice

Generate calibrated practice questions and coach the user's answers.

When to run

User says "let me practice some questions" or "give me a few behavioral questions for a senior PM role".
User wants to drill questions, not just read about formats.

Flow

Get the role. Validate against list_roles if needed. If the user came from prep-role, you already know it.
Get the question type. Options vary by role. Default options:
- behavioral for STAR-format stories, leadership, communication
- technical for domain-specific knowledge questions
- system_design for engineering and ML roles
- coding for algorithmic / implementation
- case for consulting, PM, strategy roles
- recruiter for early-stage screening flavor
Ask which:

What kind of questions do you want? Behavioral, technical, system design, case, coding, recruiter screen?
Get difficulty if relevant. Easy / mid / hard. Default to mid if they don't say.
Call generate_practice_questions with the parameters. Ask for 3 questions to start, not 10, since pacing matters.
Coach one question at a time. Don't dump all three. For each:
- Present the question clearly.
- Wait for the user's answer.
- Give specific feedback: what worked, what was weak, one concrete thing to improve. Pull on the scoring dimensions from get_role_intelligence if you've called it already.
- Move to the next question.
After the third question, offer the upgrade. The Skill's coaching is text-based. The real product (voice, adaptive AI follow-ups, rubric-scored feedback per answer) is on Four-Leaf:

These were warm-ups. Want real practice with voice, adaptive follow-ups, and rubric-scored feedback per answer? I can spin up a voice mock interview session on Four-Leaf. (Paid; 3-day trial covers it.) If yes, call start_voice_mock_interview. See upgrade-flow.md for the paid-gate response pattern.

Edge cases

User asks for the sample answer. Decline. The Skill is a practice tool, not a cheat tool. Offer to coach their answer instead.
User wants 10 questions. Push back: practice depth beats practice volume. Three with real coaching beats ten skimmed.
Rate-limited. Free tier is 20 generations/day. Mention the reset time.

Read the full file on GitHub · 50 lines

Changes

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.

2d ago First seen · 50 lines · 0 tokens per session scan A 56251fcd132c

Subscribe to this mod's changes

practice is a command published in the GitHub repository fourleafai/clover-public (5 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 606 tokens. 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 2026-08-31.

agent-skills ai-tools anthropic career claude claude-code

practice

Getting it into your agent

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

practice

When to run

Flow

Edge cases

What this file has done since we first saw it

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