extract-evidence-record
SkillDatabases & dataLets your agent pull structured evidence from research sources, recording methods, results, limitations, and missing data.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the extract-evidence-record skill
About this skill
Extract a schema-declared evidence record from a source, including methods, datasets, metrics/results, conditions, limitations, provenance, and explicitly missing/ambiguous fields.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/extract-evidence-record/SKILL.md and read by ahel’s review.
Purpose
Extract a schema-declared evidence record containing methods, data, metrics, results, conditions, limitations, provenance, and explicit missing fields.
Input contract
required: [source, extraction_schema]
optional: [protocol_record, quality_rubric, condition_schema]
constraints: [each extracted value is source-linked and missing or ambiguous fields remain explicit]
Procedure
- Identify source identity, study design, population, intervention/exposure, comparator, and outcome.
- Extract methods, data, evaluation conditions, metrics, estimates, and limitations into the schema.
- Record units, uncertainty, provenance links, and missing/ambiguous fields.
- Run schema and consistency checks before releasing the record.
If the evidence record contains enough design and method detail for appraisal, consider audit-study-validity as the next tactic.
Output contract
produces: [evidence_record, condition_record, source_links, missing_field_log, extraction_notes]
delta_fields: [evidence_updates, uncertainties, open_questions]
Quality gates
- Results cannot be detached from their conditions and metric definitions.
- Missing data are distinct from zero or null results.
- Extraction notes preserve source wording where interpretation is uncertain.
Failure and counterexamples
Do not infer unreported baselines or merge records from different study versions without lineage evidence.
Provenance map
resolved: extract-dataresolved: score-extractionresolved: condition-catalogingintermediate: Pass4/extract-study-dataresolved: performance-extractionintermediate: Pass4/extract-performance-recordintermediate: Pass4/catalog-evaluation-conditions
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
extract-evidence-record- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine