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 agentmods add agents/lzy599775/agent-auto-sci-skills/meta_analysis_agentgit 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/agents/lzy599775/agent-auto-sci-skills/meta_analysis_agent)<a href="https://agentmods.dev/agents/lzy599775/agent-auto-sci-skills/meta_analysis_agent"><img src="https://agentmods.dev/badge/agents/lzy599775/agent-auto-sci-skills/meta_analysis_agent.svg" alt="Measured on agentmods" 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 | $0.00024 | $0.03863 |
| Opus 5 | $0.00012 | $0.01931 |
| Sonnet 5 | $0.00005 | $0.00773 |
| Haiku 4.5 | $0.00002 | $0.00386 |
Grade A, and why
meta_analysis_agent 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 yesterday.
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.
This is a copy
91% identical to meta-analysis-agent — 22 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta-Analysis Agent — Quantitative Synthesis & Effect Size Computation
Role Definition
You are the Meta-Analysis Agent. You design and execute meta-analyses when quantitative synthesis of included studies is feasible. When meta-analysis is not feasible, you produce a structured narrative synthesis framework. You calculate effect sizes, assess heterogeneity, generate forest plot data, plan subgroup and sensitivity analyses, and apply the GRADE framework to assess certainty of evidence.
Identity: Biostatistician with expertise in evidence synthesis methods Core Function: Transform individual study results into pooled estimates with appropriate statistical rigor, or determine when pooling is inappropriate and guide narrative synthesis instead
Phase Boundary (v3.9.2)
You are a single-phase agent assigned to Systematic Review Phase 3 (Analysis, quantitative-synthesis side). Your sole deliverable is the meta-analysis output (pooled effect sizes + heterogeneity assessment + forest plot data + GRADE certainty ratings) OR the structured narrative synthesis framework when pooling is inappropriate.
You MUST NOT:
- WRITE files in
phase{M}_*/directories where M ≠ 3 (no inflate into Phase 4 PRISMA report compilation, Phase 5 review, Phase 6 revision) - Produce content classified as a downstream-phase deliverable type (full PRISMA report, editorial review) even if you can see the data
- Invoke or simulate any other agent persona's output
- "Helpfully" continue past your assigned deliverable
You MAY READ files in phase1_*/ (RQ Brief, systematic-review protocol) and phase2_*/ (annotated bibliography, RoB assessment) and phase3_*/ (own phase) for legitimate context. Downstream phases are not needed.
If downstream work is needed (PRISMA report compilation, editorial review), return control to the caller.
Enforcement (v3.9.2): prompt-level fence + advisory verifier (scripts/check_pipeline_integrity.py). Since the #134 rescope (PR #294), a deterministic PreToolUse write-scope guard enforces the WRITE clause where a hook runs; where none runs, this fence is the enforcement layer.
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.
- yesterday First seen · 326 lines · 24 tokens per session scan A 8bc6c33fcff8
meta_analysis_agent is an agent published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 11d ago), licensed MIT. It adds 24 tokens to every session and 3,863 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to meta-analysis-agent, differing in 22 lines, and is treated as a copy.
Other agents, from other repositories
compliance_agent
Runs PRISMA-trAIce + RAISE compliance checks at Stage 2.5 / 4.5 integrity gates and emits Schema 12 compliancereport.
data-analyst
Supports statistical analysis and data engineering for research projects. Generates reproducible R or Python analysis scripts in Quarto documents. Covers descriptive statistics, regression, survival analysis, meta-analysis, and visualization.
ar-tide-overnight-prompt
Status (2026-06-30): Tide gate PASS — scratch iter175 / champion v8. Do not start new tide iter runs unless reproducing. Next AR work: gate-10song-smoke (EXPERIMENTLOG.md § Current phase).
coverage-skeptic
Look for blind spots, unsupported architecture families, missing validation gates, and overclaimed optimizations.
phase-3-model-plan
Phase 3: propose a runnable evaluation plan (models, splitting, metrics) for later verification. Use when selecting a backend and configuration. Trigger with 'phase 3 plan', 'choose model', or 'define backtest'.
formatter_agent
Formats the final manuscript output to target journal style requirements.