Meta Analysis
Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.
Install
$ agentstack add skill-thada2402-autoresearchclaw-meta-analysis ✓ 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.
About
Meta-Analysis Best Practice
When comparing results across studies or experiments:
- Report effect sizes, not just p-values
- Use standardized metrics for cross-study comparison
- Account for heterogeneity (different setups, datasets, seeds)
- Report confidence intervals alongside point estimates
- Use forest plots to visualize cross-study comparisons
- Identify and discuss outliers or inconsistent results
- Consider publication bias when interpreting aggregate results
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: thada2402
- Source: thada2402/AutoResearchClaw
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet — be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.