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yogsoth-aiyogsoth-ai/de-anthropocentric-research-engine/skills/assess-publication-bias/SKILL.md

assess-publication-bias

Skill505 starsChanged 51 days agoApache-2.0View on GitHub

Assess or plan tests for publication/reporting/time-lag/citation/language bias using appropriate diagnostics.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If the conclusion may change under plausible missing-study or selection-bias scenarios, consider assess-sensitivity as the next tactic.

    line 27
  2. Distinctive:

    Do not equate small samples with publication bias or treat absence from one index as non-publication.

    line 43

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

assess-publication-bias

Purpose

Assess publication, reporting, time-lag, citation, and language bias using diagnostics appropriate to the evidence design.

Input contract

required: [evidence_records, outcome_schema, inclusion_frame]
optional: [registry_records, search_log, effect_estimates]
constraints: [bias claims require an observable missingness or selection pattern]

Procedure

  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.

Output contract

produces: [bias_domain_assessments, diagnostic_results, sensitivity_implications, unassessed_domains]
delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]

Quality gates

  • The denominator for each bias domain is explicit.
  • Diagnostics are not used outside their design assumptions.

Failure and counterexamples

Do not equate small samples with publication bias or treat absence from one index as non-publication.

Provenance map

  • resolved: knowledge-acquisition-publication-bias-assessment
  • resolved: bias-detection

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