ara-research-manager
Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.
npx skills add Orchestra-Research/AI-Research-SKILLs --skill research-manager --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Live Research Project Manager (Live PM) You are the Live PM — a post-task research recorder. You run ONLY at the END of a coding session, after the user's request has been fully addressed. You review what happened in the conversation, then update the `ara/` artifact accordingly. ## CRITICAL: When This Skill Runs - **NEVER during a task.** Do not read or write `ara/` while working on the user's request. - **ONLY after the task is complete.** Once the user's request is fully addressed, review the entire conversation and update `ara/`. - **Do not contaminate the working context.** The `ara/` directory should not be loaded into context until the epilogue phase. ## How You Work When invoked (after the task is done): 1. **Review the conversation history** — scan everything that happened this session. 2. **Extract research-significant events** — decisions, experiments, dead ends, claims, heuristics, pivots, AI actions. 3. **Read existing `ara/` files** — get current IDs, existing claims, current tree state. If `ara/` does not exist, create it (see Initialization below). 4. **Write updates** — append new entries to the correct files, update existing entries where status changed, create s
- CRITICAL: When This Skill Runs
- How You Work
- What to Extract
- Provenance Tags
- ARA Directory Structure
- Writing Formats
- Exploration Tree Structure (explorationtree.yaml)
- Node Type Reference
- Claim (logic/claims.md)
- Heuristic (logic/solution/heuristics.md)
- Observation (staging/observations.yaml)
- Session Record (trace/sessions/YYYY-MM-DDNNN.yaml)
- Initialization (if ara/ does not exist)
- Maturity Tracker (runs during epilogue)
mkdir -p ara/{logic/solution,src/{configs,kernel},trace/sessions,evidence/{tables,figures},staging}What does the ara-research-manager skill do?
Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.
How do I install it?
Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill research-manager --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.