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 ShaishavMaisuria/research-paper-lifecycle-skills --skill rehearse-qagit clone --depth 1 https://github.com/ShaishavMaisuria/research-paper-lifecycle-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/shaishavmaisuria/research-paper-lifecycle-skills/rehearse-qa)<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.
<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>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 | $0.00206 | $0.01803 |
| Opus 5 | $0.00103 | $0.00901 |
| Sonnet 5 | $0.00041 | $0.00361 |
| Haiku 4.5 | $0.00021 | $0.00180 |
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.
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 — 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. Aftersimulate-reviewers— its weakness list seeds the dreaded-question inventory.
Inputs
- The paper (and slides/script if they exist), in any readable form. Process them transiently — never copy paper text into this repo.
- The setting and slot: conference talk / lightning / keynote / poster / defense / job talk, plus the Q&A length in minutes (ask if unknown).
- Optional but better: a venue profile
venues/conferences/<venue>-<year>.yml(schema invenues/schema.yml) so the audience matches the venue family. No profile?parse-cfpcan create one, or run with the generic audience.
Process
-
Build the drill plan. Run:
python3 scripts/qa_drill.py --setting conference-talk --minutes 3 \ --venue venues/conferences/<venue>-<year>.ymlDeterministic 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
--venueis given), the round plan, answer-time targets, and a transcript skeleton for step 6.--jsonfor machine output;--helpfor all settings. Exit codes: 0 ok, 2 bad arguments or missing/unparsable profile.
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.
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.
- 12d ago First seen · 137 lines · 206 tokens per session scan A 019150a78b27
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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