abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Assess or plan tests for publication/reporting/time-lag/citation/language bias using appropriate diagnostics.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill assess-publication-bias -a windsurf -y
name: assess-publication-bias description: "Assess or plan tests for publication/reporting/time-lag/citation/language bias using appropriate diagnostics."
Assess publication, reporting, time-lag, citation, and language bias using diagnostics appropriate to the evidence design.
required: [evidence_records, outcome_schema, inclusion_frame] optional: [registry_records, search_log, effect_estimates] constraints: [bias claims require an observable missingness or selection pattern]
1. Define the eligible study universe and the observed evidence subset. 2. Compare availability, reporting, citation, timing, and language patterns across the declared dimensions. 3. Apply design-appropriate diagnostics and record assumptions. 4. Distinguish detected bias, plausible bias, and unassessed domains.
If the conclusion may change under plausible missing-study or selection-bias scenarios, consider `assess-sensitivity` as the next tactic.
produces: [bias_domain_assessments, diagnostic_results, sensitivity_implications, unassessed_domains] delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
Do not equate small samples with publication bias or treat absence from one index as non-publication.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Evaluate competing arguments against stated criteria and produce a reasoned verdict with uncertainty.
Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context,…
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. Perspective, target,…
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…