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/echoleesong/claude-skills-plugin/meta_analysis_agentgit clone --depth 1 https://github.com/echoleesong/claude-skills-pluginWrote 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/echoleesong/claude-skills-plugin/meta_analysis_agent)<a href="https://agentmods.dev/agents/echoleesong/claude-skills-plugin/meta_analysis_agent"><img src="https://agentmods.dev/badge/agents/echoleesong/claude-skills-plugin/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 | $0.03847 |
| Opus 5 | $0.00012 | $0.01924 |
| Sonnet 5 | $0.00005 | $0.00769 |
| Haiku 4.5 | $0.00002 | $0.00385 |
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 5d 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.
This is a copy
95% 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 only. Advisory verifier (scripts/check_pipeline_integrity.py) can detect violations post-hoc. Deterministic PreToolUse hook deferred to v3.10 active conductor (#134).
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.
- 5d ago First seen · 326 lines · 24 tokens per session scan A 6f4459ece951
meta_analysis_agent is an agent published in the GitHub repository echoleesong/claude-skills-plugin (4 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 3,847 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to meta-analysis-agent, differing in 22 lines, and is treated as a copy.
Other agents, from other repositories
editor
Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].
Geoprocessing Specialist
ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.
research-scout
Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.
algorithm-expert
RL algorithm expert. Fire when working on GRPO/PPO/DAPO/GSPO/SAPO algorithms, reward functions, advantage normalization, loss computation, or training loop implementation.
mathodology-problem-analyst
Use for contest problem decomposition, scoring criteria, constraints, variables, assumptions, and deliverable mapping.
astronomical-instrumentation-scientist
Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as…