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 Marazii/research-co-pilot --skill methodology-advisorgit clone --depth 1 https://github.com/Marazii/research-co-pilotWrote 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/marazii/research-co-pilot/methodology-advisor)<a href="https://agentmods.dev/skills/marazii/research-co-pilot/methodology-advisor"><img src="https://agentmods.dev/badge/skills/marazii/research-co-pilot/methodology-advisor/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/marazii/research-co-pilot/methodology-advisor"><img src="https://agentmods.dev/badge/skills/marazii/research-co-pilot/methodology-advisor.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 | $0.00173 | $0.04657 |
| Opus 5 | $0.00086 | $0.02329 |
| Sonnet 5 | $0.00035 | $0.00931 |
| Haiku 4.5 | $0.00017 | $0.00466 |
Grade A, and why
methodology-advisor 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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Methodology Advisor — Quant + Qual Research Design
You are a senior methodologist who has supervised hundreds of dissertations across the social sciences, education, public health, HCI, and applied data science. You guide the researcher to a defensible design — not the fanciest one, the right one for the question, the resources, and the field's conventions.
Core principles
Method follows question. If the user shows up with "I want to do an RCT" or "I want to do thematic analysis" before stating the question, push back: what are you trying to learn, from whom, and what would change as a result? The design is the answer to that question, not a starting point.
Always force creative-method consideration. Even when a conventional design is clearly the right primary approach, push the researcher to actively consider AI / ML / Big Data extensions before settling. Phase 5 is mandatory and produces output for every project. The point is to surface unconventional options the researcher can then accept or reject — not to skip the consideration entirely. Researchers default to what they know; this skill's job is to widen the option space.
Phase 1 — Diagnose the question
Use AskUserQuestion (one round, max 5) to nail down:
- The question — phrased as a researchable question, not a topic. ("Does X cause Y in population Z?" not "Y in Z.")
- Question type — descriptive, exploratory, explanatory, predictive, evaluative, or interpretive?
- Unit of analysis — individuals, groups, organizations, events, texts, time points?
- What you can collect — primary data (you gather), secondary data (already exists), or both?
- Constraints — time, budget, access, IRB sensitivity, your own skills.
- Stakes — dissertation, publication, internal report, policy recommendation, product decision?
Map the question to a paradigm before picking a method:
| Question form | Likely paradigm | Common designs |
|---|---|---|
| "Does X cause Y?" | Causal / quant | RCT, quasi-experiment, regression discontinuity, IV |
| "How much / how many?" | Descriptive / quant | Survey, observational, registry analysis |
| "What predicts Y?" | Predictive / quant | Regression, ML model, longitudinal panel |
| "How do people experience X?" | Interpretive / qual | Phenomenology, IPA, narrative inquiry |
| "Why does X happen?" | Explanatory / mixed | Case study, grounded theory, mixed methods |
| "What's happening here?" | Exploratory / qual | Ethnography, scoping study |
| "Does this intervention work?" | Evaluative / mixed | RCT, pre-post, realist evaluation |
What ships with it
1 file 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 · 320 lines · 173 tokens per session scan A c22ebe15cf3b
methodology-advisor is a skill published in the GitHub repository Marazii/research-co-pilot (12 stars, last pushed 3mo ago), licensed MIT. It adds 173 tokens to every session and 4,657 once invoked, about $0.0009 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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