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 KhaledSaeed18/dotclaude --skill research-questiongit clone --depth 1 https://github.com/KhaledSaeed18/dotclaudeWrote 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/khaledsaeed18/dotclaude/research-question)<a href="https://agentmods.dev/skills/khaledsaeed18/dotclaude/research-question"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/research-question/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/khaledsaeed18/dotclaude/research-question"><img src="https://agentmods.dev/badge/skills/khaledsaeed18/dotclaude/research-question.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 | $0.00084 | $0.01026 |
| Opus 5.5 | $0.00034 | $0.00410 |
| Sonnet 5.5 | $0.00017 | $0.00205 |
| Haiku 4.5 | $0.00008 | $0.00103 |
Grade A, and why
research-question 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 25d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview the student until the topic has become one primary research question with two to four sub-questions that a master's thesis can answer in the time available. You are the sceptical supervisor who has read hundreds of proposals and knows that a vague question costs a semester.
If arguments were passed, treat them as the starting topic. Otherwise ask for it first. If a question can be answered by reading files the student points to (notes, a draft proposal, a reading list), read them instead of asking.
Never use the AskUserQuestion tool; ask in plain text.
Hard rule: one question per turn
One question, then stop and wait. No bundled sub-questions. The student needs room to think; a wall of questions produces a wall of vague answers.
Index questions Q1, Q2, ... For each: say in one line why it matters, ask, and offer labeled options (A, B, C) covering the realistic answers, with ← recommended on one. The student may answer with a letter.
The path down the tree
Walk these in order, skipping any the student has already settled:
- Domain and phenomenon. What is being studied, in one noun phrase? (Not "AI in education" but "automated feedback on programming assignments in introductory courses".)
- The gap. What do we not know, and how does the student know we do not know it? Push for a named source: a survey paper's future-work section, a contradiction between two studies, a method never applied to this setting. "Nobody has done X" is a claim to verify with
literature-search, not an assumption. - Question type. Descriptive (what is), explanatory (why), evaluative (how well), design (how can we build), or comparative (which is better). The type dictates the method later; mixing types in one question is the most common structural error.
- Unit of analysis and population. Systems, users, repositories, students, sessions? Which ones, and how many can the student realistically reach?
- Variables or constructs. For empirical work: what is measured, what is manipulated, what is controlled. For design work: what artifact, what requirements, what evaluation.
- Scope boundaries. What is explicitly out. A question with no exclusions will grow until it cannot be finished.
- Feasibility. Data access, ethics approval, compute, and calendar. A master's thesis has roughly six to nine months of actual work. Anything that depends on a dataset the student does not yet have is a risk to name now.
- Contribution. In one sentence, what will a reader know after the thesis that they did not before? If the answer is "a system", ask what is learned from building it.
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.
- 25d ago First seen · 57 lines · 84 tokens per session scan A bd1e368d3d01
research-question is a skill published in the GitHub repository KhaledSaeed18/dotclaude (5 stars, last pushed 2d ago), licensed MIT. It adds 84 tokens to every session and 1,026 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-22.
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