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orcaid
OrCAID multi-agent execution engine — correct entry (orcaid.cli), local path support, auto-build Docker, three task types (commit0/self_improve/paperbench)
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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OrCAID multi-agent execution engine — correct entry (orcaid.cli), local path support, auto-build Docker, three task types (commit0/self_improve/paperbench)
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
arXiv paper discovery — select top 3 significant papers, research via subagents, ingest to wiki, deliver report.
Daily raw file ingestion pipeline — process files from raw/ into structured wiki knowledge, verify frontmatter and links, archive to Clippings/. Schedule: 06:30 AM.
Daily Zettelkasten insight generation — run CLI insight engine, create wiki pages for confidence>=0.7 insights, integrate to wiki. Schedule: 06:00 AM.
Daily global news curator — RSS discovery, significance filtering, clippings archive + synthesis wiki delivery, deliver headlines report. Schedule: 07:30 AM.
Wiki synthesis agent operational sheet — cross-domain bridges, concept advancement, evidence evaluation
Daily wiki quality audit anchored in wiki-indexing-theory.md — HITS authority scoring, GAAC cluster validation, tag taxonomy compliance, reciprocal link enforcement. Schedule: 08:50 AM.
| type | skill-manual |
| name | orcaid |
| description | OrCAID multi-agent execution engine — correct entry (orcaid.cli), local path support, auto-build Docker, three task types (commit0/self_improve/paperbench) |
| triggers | ["run OrCAID","commit0","self_improve","paperbench","add OrCAID task"] |
| tags | ["orcaid","multi-agent","delegation"] |
| updated | "2026-05-24T00:00:00.000Z" |
Cron
297092f3b347is PAUSED. This skill is manual-only — run on-demand via CLI.
Repo: /home/ty/Repositories/ai_workspace/OrCAID/
Always use uv run python -m orcaid.cli — NOT run_infer.py, NOT bare python.
cd /home/ty/Repositories/ai_workspace/OrCAID
uv run python -m orcaid.cli [flags...]
.env file at OrCAID root sets LLM_MODEL and LLM_BASE_URL.
cd /home/ty/Repositories/ai_workspace/OrCAID
uv run python -m orcaid.cli \
--task=commit0 \
--repo /home/ty/Repositories/ai_workspace/Paper2Code-Enhanced \
--model minimax/MiniMax-M2.7 \
--multi_agent=false \
--max_iterations=5
cd /home/ty/Repositories/ai_workspace/OrCAID
uv run python -m orcaid.cli \
--task=self_improve \
--repo_path /home/ty/Repositories/ai_workspace/OrCAID \
--task_description "Add memory-of-failures pattern to Manager._verify_and_return" \
--model minimax/MiniMax-M2.7 \
--multi_agent=false \
--max_iterations=3
uv run python -m orcaid.cli \
--task=paperbench \
--paper_id 2605.18703 \
--model minimax/MiniMax-M2.7 \
--multi_agent=false \
--max_iterations=5
arXiv cron (arxiv agent) → saves papers to arxiv-papers/
↓
Paper2Code-Enhanced (your CLI) → generates code repo
↓
OrCAID commit0 → validates + fixes generated repo
This pipeline runs on-demand, not on a cron schedule. Paper2Code generates; commit0 validates.
--repo accepts absolute local paths (starting with /). When given a local path:
python:3.12-slim, Node → node:20-slim, etc.)# Local path — container builds from python:3.12-slim automatically
uv run python -m orcaid.cli \
--task=commit0 \
--repo /home/ty/Repositories/ai_workspace/Paper2Code-Enhanced \
--model minimax/MiniMax-M2.7
Docker must be running. OrCAID uses openhands.workspace.DockerDevWorkspace:
openhands.workspace.DockerDevWorkspace builds images from base_image (not from the target repo)base_image is set by task_module.get_workspace_config()["base_image"]python:3.12-slimbuild() function builds from the base imageUse
--docker_image=docker.io/wentingzhao/minitorch:v0only when you specifically need the minitorch image.
| Flag | Task | Purpose |
|---|---|---|
--task | all | commit0, self_improve, paperbench |
--repo | commit0 | GitHub URL (owner/repo) or local absolute path |
--repo_path | self_improve | Local absolute path to the repo |
--model | all | LiteLLM model (minimax/MiniMax-M2.7) |
--multi_agent | all | true (4 engineers) or false (single agent) |
--max_iterations | all | Max Manager LLM turns |
--max_rounds_chat | all | Subagent chat rounds (default: 2) |
--paper_id | paperbench | arXiv paper ID |
| Path | Role |
|---|---|
/home/ty/Repositories/ai_workspace/OrCAID/ | OrCAID repo root |
/home/ty/Repositories/ai_workspace/Paper2Code-Enhanced/ | Target repo for commit0 |
~/.hermes/orchestrator-memory/verified/ | Verified SubAgentResult outcomes |
~/.hermes/orchestrator-memory/drift_logs/ | Drift/failure records |
~/.hermes/orchestrator-memory/escalations/ | Human review items |
~/.hermes/orcaid-bridge/ | Bridge storage |
| File | Role |
|---|---|
orcaid/cli.py | Entry point — DockerDevWorkspace setup + workflow |
orcaid/core/utils.py | build_task_module() (line 1309), build_llm_kwargs() |
orcaid/core/manager.py | Manager + _verify_and_return() (lines 678, 710, 731) |
orcaid/core/subagent.py | SubAgentRunner — git worktree per engineer |
orcaid/tasks/commit0.py | commit0: pytest, stub implementations |
orcaid/tasks/self_improve.py | self_improve: ast.parse syntax check |
orcaid/tasks/paperbench.py | paperbench: LLM judge evaluation |
orcaid/tasks/paper2code.py | PaperCoder task (stub, wired but not implemented) |
orcaid_verification_bridge.py | Self-healing: verify_subagent_completion() |
| Task | Kwarg mapping |
|---|---|
commit0 | repo → repo_name, also base_branch, docker_image_prefix, docker_image, dataset_path |
self_improve | repo_path, task_description |
paperbench | paper_id, docker_image, paperbench_dir, ... |
paper2code | repo_path, paper_url, output_dir (wired but stub) |
# In OrCAID .env
LLM_MODEL=minimax/MiniMax-M2.7
LLM_BASE_URL=https://api.minimax.io/v1
LLM_API_KEY=<key>
Must be /v1, not /anthropic/v1/messages.
User → orcaid.cli → build_task_module() → TaskModule
↓
DockerDevWorkspace (base_image=python:3.12-slim, target=source-minimal)
↓ (OpenHands builds image + starts container)
container: copy local repo → run agent (Manager + Engineers)
↓
Manager: scan_and_analyze() → delegate_tasks() → run_subagents_parallel()
↓
collect_and_merge() → _verify_and_return()
→ bridge.verify_subagent_completion()
→ PASS: orchestrator-memory/verified/
→ FAIL: orchestrator-memory/drift_logs/ + correction_context
↓
final_review_all() → outputs/
Key line references:
orcaid/core/manager.py lines 678, 710, 731: _verify_and_return()orcaid/core/utils.py line 1309: build_task_module()| Symptom | Cause | Fix |
|---|---|---|
| Exit 1, no output | Missing .env or Docker not running | Check LLM_BASE_URL, docker ps |
| "Unknown model provider" | Wrong LLM_BASE_URL | Must be https://api.minimax.io/v1 |
| Local path not copied | Path must be absolute (start with /) | Use /home/ty/... not ~/... |
| No container starts | Docker not running | docker ps to verify |
paper2code task fails | evaluate() is still a stub | Implement evaluation or use commit0 on the generated repo instead |
tasks/my_task.py: MyTaskConfig dataclass + MyTask(TaskModule) implementing:
get_docker_image(), get_work_dir(), get_workspace_config()load_task_data(), setup_workspace(), evaluate()tasks/__init__.py: add from .my_task import MyTaskConfig, MyTaskorcaid/core/utils.py build_task_module(): add elif task == "my_task": return MyTask(MyTaskConfig(**init))