Agent Research Aggregator
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor...
Install
npx skills add Ar9av/PaperOrchestra --skill agent-research-aggregator -g -a claude-code -y- Repository
- Ar9av/PaperOrchestra694
- Category
- AI and agents
- Updated
- 24d ago
- License
- See repository
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.
agent-research-aggregator
Should I run? (decision gate)
Before starting Phase 1, check whether aggregation is actually needed:
| Situation | Action |
|---|---|
workspace/inputs/idea.md and workspace/inputs/experimental_log.md both exist and are non-empty | Skip this skill entirely. Proceed directly to paper-orchestra. |
| Either file is missing or empty, and the user provided a directory path | Run this skill with that directory as --search-roots. |
| Either file is missing or empty, and no directory was provided | Scan cwd and ~ by default; show the discovery summary to the user before continuing. |
| The inputs exist but look thin (e.g. idea.md has < 5 lines, no numeric data in experimental_log.md) | Ask the user whether to supplement with aggregation or proceed as-is. |
The skill is intentionally a pre-pass, it is cheap to skip and should only run when the structured inputs don't already exist.
A pre-processing skill for PaperOrchestra (arXiv:2604.05018). Reads scattered
experimentation artifacts from AI coding-agent cache directories and synthesizes
them into the structured (I, E) input pair the PaperOrchestra pipeline expects.
