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 Vambrocop/EvidenceForge --skill evidence-synthesis-forgegit clone --depth 1 https://github.com/Vambrocop/EvidenceForgeWrote 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/vambrocop/evidenceforge/evidence-synthesis-forge)<a href="https://agentmods.dev/skills/vambrocop/evidenceforge/evidence-synthesis-forge"><img src="https://agentmods.dev/badge/skills/vambrocop/evidenceforge/evidence-synthesis-forge/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/vambrocop/evidenceforge/evidence-synthesis-forge"><img src="https://agentmods.dev/badge/skills/vambrocop/evidenceforge/evidence-synthesis-forge.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 | $0.00065 | $0.00937 |
| Opus 5.5 | $0.00026 | $0.00375 |
| Sonnet 5.5 | $0.00013 | $0.00187 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
evidence-synthesis-forge 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 1mo 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evidence Synthesis Forge
Use this skill as the general orchestrator for evidence synthesis. It helps move from a broad review idea to an auditable protocol, screening workflow, extraction plan, synthesis strategy, and report structure.
Core Principle
Separate:
- Question: what evidence is being synthesized.
- Search: how studies are found.
- Screening: how studies are included or excluded.
- Coding: how study features and effects are extracted.
- Synthesis: whether evidence is narratively summarized, mapped, or statistically pooled.
- Judgment: risk of bias, certainty, and interpretation.
Do not jump to meta-analysis before checking whether studies, outcomes, and effect sizes are comparable.
Intake
Identify:
- domain: environment, ecology, medicine, life science, economics, policy, education, psychology, or other;
- review type: systematic review, scoping review, evidence map, rapid review, meta-analysis, umbrella review, or second-order meta-analysis;
- question framework: PICO, PECO, PICOS, SPIDER, or custom;
- population/exposure/intervention/comparator/outcome;
- eligible study designs;
- desired outputs;
- whether machine learning will assist screening or extraction.
If the user is unsure, propose a review type and explain the tradeoff.
Workflow
- Build the review question.
- Define eligibility criteria.
- Draft search strategy and databases.
- Design screening stages and exclusion reasons.
- Define extraction fields and coding rules.
- Choose synthesis type: narrative, evidence map, first-order meta-analysis, umbrella review, or second-order meta-analysis.
- Specify risk-of-bias or quality assessment.
- Align the protocol and report with the relevant guidance source: PRISMA for reporting, Cochrane for intervention reviews, JBI for broader review types, CEE for environmental evidence.
- Add reproducibility artifacts: search log, screening log, coding sheet, analysis script, protocol.
Load:
references/review-types.mdwhen the user needs help choosing review type or question framework.references/protocol-reporting-crosswalk.mdwhen the user needs PRISMA/Cochrane/JBI/CEE alignment.templates/prisma-flow-counts.csvandscripts/generate_prisma_flow.pywhen the user needs a simple reproducible PRISMA-style flow diagram.
What ships with it
5 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.
- 1mo ago First seen · 122 lines · 65 tokens per session scan A ba83c1b315e9
evidence-synthesis-forge is a skill published in the GitHub repository Vambrocop/EvidenceForge (7 stars, last pushed 8d ago), licensed MIT. It adds 65 tokens to every session and 937 once invoked, about $0.0003 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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