rehearse-qa

rehearse-qa is a skill for Claude Code from ShaishavMaisuria/research-paper-lifecycle-skills. It costs 206 tokens per session (1,803 once invoked), scanned A, original, Apache-2.0.

A practice session that simulates questions from an audience at a conference talk, thesis defense, job talk, or poster session.

In plain words
What is it for?
It helps anticipate difficult questions, practise answers from a paper and slides, prepare for hostile or curious audiences, and rehearse different presentation formats.
Why use it?
Unplanned questions can expose weak explanations or claims the speaker has not prepared to defend. It asks grounded questions one at a time and coaches concise, honest answers.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the paper-presenting plugin — 4 skills shipped together

Good fit It helps anticipate difficult questions, practise answers from a paper and slides, prepare for hostile or curious audiences, and rehearse different presentation formats.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa
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.

Any agent
npx skills add ShaishavMaisuria/research-paper-lifecycle-skills --skill rehearse-qa
Clone the repo
git clone --depth 1 https://github.com/ShaishavMaisuria/research-paper-lifecycle-skills

Made for: Claude Code.

Or install paper-presenting, the plugin that ships this one along with the rest of its 4 skills.

Wrote 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.

agentmods badge for rehearse-qa

README.md
[![agentmods](https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa/github.svg)](https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa)
Your own site
<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa/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.

agentmods 80×15 button for rehearse-qa

Your own site · 80×15
<a href="https://agentmods.dev/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa"><img src="https://agentmods.dev/badge/skills/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 206 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,803 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00206 $0.01803
Opus 5 $0.00103 $0.00901
Sonnet 5 $0.00041 $0.00361
Haiku 4.5 $0.00021 $0.00180

Measured 12d ago against content hash 019150a78b27, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

rehearse-qa 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 12d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/grade_answers.py, scripts/qa_drill.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/rehearse-qa/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rehearse Q&A

Drill the Q&A session before it happens. A simulated audience — hostile and curious personas calibrated to the venue — asks questions one at a time, grounded in the user's actual paper and slides; every answer gets coached into a concise, honest, answer-first response; the questions the speaker hopes nobody asks get prepared deliberately instead of dreaded vaguely.

When to use

  • "Grill me on my paper" / "rehearse the Q&A for my talk" / "mock Q&A"
  • "What will the audience ask?" / "what's the worst question I could get?"
  • "Practice my thesis defense / viva" / "prep me for job-talk questions"
  • Poster-session prep (continuous Q&A, 2-minute and 5-minute pitches)
  • After write-talk-script / make-slides — the talk is built, now the unscripted part gets rehearsed. After simulate-reviewers — its weakness list seeds the dreaded-question inventory.

Inputs

  1. The paper (and slides/script if they exist), in any readable form. Process them transiently — never copy paper text into this repo.
  2. The setting and slot: conference talk / lightning / keynote / poster / defense / job talk, plus the Q&A length in minutes (ask if unknown).
  3. Optional but better: a venue profile venues/conferences/<venue>-<year>.yml (schema in venues/schema.yml) so the audience matches the venue family. No profile? parse-cfp can create one, or run with the generic audience.

Process

  1. Build the drill plan. Run:

    python3 scripts/qa_drill.py --setting conference-talk --minutes 3 \
        --venue venues/conferences/<venue>-<year>.yml
    

    Deterministic and offline. Emits the slot math (how many questions the live slot actually fits, how many to drill), the persona lineup with per-persona quotas (venue-family calibrated when --venue is given), the round plan, answer-time targets, and a transcript skeleton for step 6. --json for machine output; --help for all settings. Exit codes: 0 ok, 2 bad arguments or missing/unparsable profile.

Read the full file on GitHub · 137 lines

Files

What ships with it

5 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.

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.

  1. 12d ago First seen · 137 lines · 206 tokens per session scan A 019150a78b27

Subscribe to this mod's changes

rehearse-qa is a skill published in the GitHub repository ShaishavMaisuria/research-paper-lifecycle-skills (42 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 206 tokens to every session and 1,803 once invoked, about $0.0010 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 2026-08-30.

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