Primary guidance and review limits

Reviewed 2026-10-01. This is an evidence-appraisal workflow, not an implementation of formal scoring algorithms, a statistical package, or a clinical decision system. Use the complete current tool documents for a formal assessment and retain version/date, result identity, source locations, signalling answers, and judgment rationale.

Risk of bias, reporting, and certainty

The GRADE Book is replacing the older handbook progressively. Its three chapters above were read through rendered-page extraction because ordinary HTTP/browser text returned a JavaScript shell. The newer threshold/range framing should not be replaced with the older shortcut that certainty only means closeness to a point estimate.

Statistical and causal appraisal

• ASA p-value statement: p-values do not give hypothesis probabilities, effect importance, or a complete basis for decisions. Interpretation requires the analysis context and full reporting.
• Greenland et al., statistical misinterpretations: test statistics and confidence intervals depend on the full model and sampling/selection assumptions; avoid observed-power, threshold, and interval-overlap shortcuts.
• Hernán and Robins, Causal Inference: What If: define the causal estimand and defend consistency, exchangeability, positivity, and selection assumptions. The authors' current book link is dated August 19, 2026.
• Cochrane Handbook, chapter 13: missing-evidence appraisal cannot be reduced to a funnel plot. Asymmetry has alternative explanations; tests usually require at least ten studies and appropriate effect measures.
• ARRIVE 2.0 experimental-unit explanation: state the independent unit and avoid treating subsamples or repeated measurements as additional independent experimental units.
• FDA multiple-endpoints guidance: supports specifying endpoint families and multiplicity strategies in human drug/biologic trials; its regulatory scope is not a universal rule for all exploratory science.
• WMA Declaration of Helsinki: current 2024 revision concerns medical research involving human participants. Institutional review and applicable local requirements must be checked; this skill certifies no compliance.

Executed checks and limits

• The skill contains no scripts, SDK calls, scientific API endpoints, or statistical computation engine. References to REDCap, Qualtrics, registries, and statistical software identify possible workflow tools; they are not integrations or tested instructions.
• Tiny known-answer arithmetic checks verify the illustrative predictive values and independent multiple-testing probability; they do not establish diagnostic performance in a real population or validate a formal risk-of-bias/GRADE assessment.
• The optional scientific-schematics command was checked at the local CLI/help boundary. No paid generation of that example or private-data transmission was performed. Its provider contract and dependencies belong to that skill, not this appraisal workflow.
• No patient data, clinical study, registry submission, or authenticated scientific service was accessed. Human clinical/policy decisions require the applicable professional process.