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 Lzy599775/agent-auto-sci-skills --skill agent-auto-sci-methodologygit clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-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/lzy599775/agent-auto-sci-skills/agent-auto-sci-methodology)<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/agent-auto-sci-methodology"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/agent-auto-sci-methodology/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/lzy599775/agent-auto-sci-skills/agent-auto-sci-methodology"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/agent-auto-sci-methodology.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 | $0.00104 | $0.00677 |
| Opus 5.5 | $0.00042 | $0.00271 |
| Sonnet 5.5 | $0.00021 | $0.00135 |
| Haiku 4.5 | $0.00010 | $0.00068 |
Grade A, and why
agent-auto-sci-methodology 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 27d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Auto Sci Methodology
Use this subskill when the research logic itself is uncertain or needs strengthening.
Fast Workflow
- Convert broad interests into answerable research questions.
- Define concepts, constructs, variables, mechanisms, and scope.
- Generate competing hypotheses or explanations.
- Choose design: review, observational, quasi-experimental, modeling, or mixed methods.
- Audit bias, confounding, validity, and evidence strength.
- Convert critique into concrete changes.
Read references/research_methodology_workflows.md.
Empirical support and exchangeability
Treat empirical support, positivity, and overlap as support-domain diagnostics: they identify where the observed data contain sufficiently comparable treatment variation. They do not by themselves establish conditional exchangeability. Strong overlap does not rule out unmeasured confounding, and rich covariate adjustment does not automatically prove exchangeability. Weak overlap limits which treatment contrasts are identifiable or transportable without extrapolation. Do not describe a local support screen as causal identification proof; causal interpretation also requires the design-specific identification assumptions to be credible.
For full paper projects, this skill owns topic selection, SMART research questions, hypothesis design, innovation diagnosis, feasibility, scope boundaries, conceptual framework, and reviewer-risk logic. When the task spans the whole manuscript lifecycle, coordinate through auto-sci-research/references/08_full_research_to_manuscript_pipeline.md.
For deeper K-Dense-style encapsulation:
references/k_dense_methodology_mapping.md: how hypothesis generation, critical thinking, scholar evaluation, and peer-review logic are adapted.references/sport_geography_methodology_playbook.md: sport geography research questions, spatial justice, exposure mechanisms, bias, and evidence-grading playbook.
Related Helper Skills
hypothesis-generationscientific-brainstormingscientific-critical-thinkingscholar-evaluationstatistical-analysissport-geography-review-bibliometric
What ships with it
4 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.
- 27d ago Changed · +7 lines 8eb43b50f586
- 1mo ago First seen · 44 lines · 104 tokens per session scan A 4bce24a87538
agent-auto-sci-methodology is a skill published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 104 tokens to every session and 677 once invoked, about $0.0004 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 2026-08-31.
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