Agent Auto Sci Methodology
研究方法论与批判性思维子 skill。用于研究问题 SMART 化、假设生成、机制框架、实验/准实验/观察研究设计、系统综述方法、证据质量评价、偏倚识别、因果边界、理论贡献、空间正义框架和审稿前风险扫描。触发于 hypothesis generation、research design、scientific critical thinking、evidence grading、bias audit、method critique 等任务。
Install
$ agentstack add skill-lzy599775-agent-auto-sci-skills-agent-auto-sci-methodology ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-lzy599775-agent-auto-sci-skills-agent-auto-sci-methodology) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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.
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
Must Not Do
- Do not turn a concept into a measurable variable without stating assumptions.
- Do not treat correlation, SHAP importance, or bibliometric co-occurrence as causal proof.
- Do not claim equity or justice from distribution maps alone.
- Do not hide uncertainty in policy language.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Lzy599775
- Source: Lzy599775/agent-auto-sci-skills
- License: MIT
- Homepage: https://lzy599775.github.io/agent-auto-sci-skills/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.