Evidence synthesis
Conduct a reproducible cross-domain review of multiple sources and produce an Evidence Synthesis with a protocol, search and screening record, evidence table, quality and applicability assessment, conflicts or heterogeneity, calibrated certainty, and claim boundaries. Use for systematic, rapid, scoping, or structured evidence reviews across research, policy, science, engineering, or operations. Do not use for market or competitor recommendations, summarizing one supplied source, root-cause hypothesis analysis, adjudicating one disputed claim, or collecting references without synthesis.From its SKILL.md
npx -y skills add SylphxAI/skills --skill evidence-synthesisAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 24 days oldThe repository was created 24 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
4.8 KB, 830 tokens by cl100k_base, as published. Nobody here has run it
Evidence Synthesis
Produce one Evidence Synthesis whose coverage, exclusions, conflicts, and certainty can be audited and reproduced. Read references/reproducible-evidence-synthesis.md before defining the review protocol.
Method
- Frame the answerable question, intended decision, population/system/context, intervention or exposure where relevant, outcomes, time horizon, scope, and claim boundary. Define what evidence could change the conclusion.
- Predeclare a proportionate protocol: review type, sources, search strings, dates, languages, inclusion/exclusion rules, deduplication, screening, extraction fields, quality assessment, synthesis method, and deviations.
- Search multiple appropriate channels. Preserve exact queries, filters, timestamps, result counts, unavailable sources, and citation chaining. Prefer primary studies or original records while using reviews to locate and contextualize them.
- Screen against declared criteria. Record reasons for material exclusions. Use independent duplicate screening or targeted second review when a consequential inclusion judgment is ambiguous; do not add ceremony when a deterministic criterion resolves it.
- Extract comparable facts into an evidence table: source identity, design, context/sample, intervention/exposure, comparator, outcome, estimate, uncertainty, limitations, funding/conflicts, and applicability.
- Assess risk of bias, source dependence, measurement validity, missingness, selective reporting, indirectness, precision, consistency, and relevance using a framework suited to the domain. Do not count repeated reports of one underlying dataset as independent evidence.
- Synthesize results. Preserve direction, magnitude, uncertainty, conflicts, and heterogeneity. Pool quantitatively only when the measures and contexts make the result meaningful; otherwise use a structured qualitative synthesis.
- State conclusion, certainty, applicability, evidence gaps, and exact limits. Separate absence of evidence from evidence of no effect and association from causation.
Output contract
Produce an Evidence Synthesis containing:
- question, decision use, scope, review type, protocol, and deviations;
- search log with sources, exact queries, dates, filters, coverage, and access limitations;
- screening flow and inclusion/exclusion reasons;
- evidence table with provenance, design, context, measures, findings, uncertainty, quality, dependence, and applicability;
- conflict, heterogeneity, bias, missing-evidence, and sensitivity analysis;
- synthesis by outcome or claim, including contrary and null evidence;
- calibrated certainty and the strongest supportable claim boundary; and
- evidence gaps, update triggers, and next research that has positive expected information value.
Integrity rules
- Freeze the protocol before reading toward a preferred conclusion; record any justified amendment rather than silently changing criteria.
- Search-result rank, citation count, prestige, repetition, and agent consensus are not independent evidence quality.
- PRISMA improves transparent reporting; it does not itself prove review quality, causal validity, or certainty.
- Do not fabricate inaccessible methods, sample sizes, effect estimates, quotations, or conclusions from titles and abstracts.
- Do not average incompatible evidence until disagreement disappears.
- A rapid review may narrow scope or duplicate work explicitly; it may not hide the resulting uncertainty.
Boundaries
market-research-synthesisowns market, category, competitor, positioning, pricing, or demand recommendations.critical-analysisowns competing hypotheses and diagnosis for one uncertain material question.evidence-and-claims-standardowns the verdict on one material or disputed factual, completion, causality, or delivery claim.causal-inference-analysisowns identification and estimation of a causal effect from data; this Skill may synthesize multiple causal studies without replacing their identification analyses.- A domain Skill owns domain-specific interpretation and decisions that consume this synthesis.