Ara Compiler
Skill Verifiziert AktivCompiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.
To transform raw research materials into a falsifiable, agent-traversable knowledge package, enabling structured analysis and reproducibility.
Funktionen
- Compiles diverse research inputs (PDFs, repos, logs, notes)
- Generates ARA with cognitive and physical layers
- Creates exploration graph and grounded evidence
- Handles partial inputs gracefully and asks for clarification
- Validates generated ARA artifacts
Anwendungsfälle
- Ingesting a research paper or codebase into a structured knowledge package.
- Building an Agent-Native Research Artifact from scratch.
- Converting research outputs into a falsifiable, agent-traversable form.
- Organizing and structuring scattered research notes and findings.
Nicht-Ziele
- Generating novel research claims or hypotheses not present in the source material.
- Performing active research or experimentation beyond artifact compilation.
- Replacing the human researcher's critical analysis or interpretation.
Workflow
- Read all provided inputs thoroughly.
- Reason through the 4-stage epistemic chain-of-thought (deconstruction, mapping, stubbing, graph extraction).
- Generate all mandatory ARA files.
- Perform a coverage check loop (max 3 rounds) to identify and patch gaps.
- Validate the ARA using Seal Level 1 checks.
- Fix any validation failures and re-validate.
- Report a summary of the generated artifact and validation result.
Practical Utility
- info:Usage examplesWhile the SKILL.md describes input handling strategies, concrete, end-to-end runnable examples demonstrating invocation and observable outcomes are not explicitly provided.
Installation
Zuerst Marketplace hinzufügen
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs/plugin install AI-Research-SKILLs@ai-research-skillsQualitätspunktzahl
VerifiziertVertrauenssignale
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