Yif-Yang
79 lines
3.4 KiB
Markdown
79 lines
3.4 KiB
Markdown
# SkillOpt-Sleep — Devin integration
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Give **Devin** (Cognition) a nightly **sleep cycle** via a tiny **MCP server**
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that exposes the `skillopt_sleep` engine as tools. MCP is Devin's supported way
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to add custom tooling, so this works in Devin's CLI and IDE.
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Devin doesn't write transcripts in the format the engine consumes, so this
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plugin adds a **Devin-specific harvester** that converts every locally available
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source into the Claude Code-compatible JSONL the engine reads.
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## What's here
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| File | Purpose |
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| `mcp_server.py` | stdlib-only MCP (stdio) server exposing `sleep_*` tools |
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| `harvest_devin.py` | converts Devin ATIF-v1.7 transcripts + agentmemory + `.devin/skills` into JSONL, with `taskKey` + outcome envelopes |
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| `judge.py` | reference judge for the deferred/judge branch of the validation gate |
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| `mcp-config.example.json` | drop-in MCP server config |
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| `devin-rules.snippet.md` | paste into `.devin/rules/skillopt-sleep.md` |
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## What it harvests
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| Source | Where |
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| Devin transcripts (ATIF-v1.7) | `~/.local/share/devin/cli/transcripts/*.json` |
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| agentmemory | `~/.agentmemory/standalone.json` |
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| Skill files | `.devin/skills/*/SKILL.md` |
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Workspaces are auto-detected from `~/.config/Devin/User/workspaceStorage/*/workspace.json`.
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After `sleep_adopt`, the evolved skill is synced to `.devin/skills/skillopt-sleep-learned/SKILL.md`.
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## Install
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Requires Python ≥ 3.10. No third-party packages — the server is pure stdlib.
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1. **Register the MCP server.** Use `mcp-config.example.json` as a template; set
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`args` to the absolute path of this `mcp_server.py`. The engine is found
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automatically (this plugin lives inside the SkillOpt repo). Or via the Devin
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CLI:
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```bash
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devin mcp add skillopt-sleep \
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--env "SKILLOPT_DEVIN_CLAUDE_HOME=$HOME/.skillopt-sleep-devin" \
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-- python3 /abs/path/to/SkillOpt/plugins/devin/mcp_server.py
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```
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2. **(Optional)** copy `devin-rules.snippet.md` to `.devin/rules/skillopt-sleep.md`
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so Devin proactively offers the tools.
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3. Ask Devin: *"run the sleep cycle"*, *"what did the last sleep propose?"*, *"adopt it"*.
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## Tools
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| Tool | What it does |
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| `sleep_status` | nights run so far + latest staged proposal |
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| `sleep_dry_run` | preview cycle — no staging; a real backend still makes provider calls |
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| `sleep_run` | full cycle; stages a proposal for review |
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| `sleep_adopt` | apply the staged proposal; syncs skill to the workspace |
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| `sleep_harvest` | debug: list the recurring tasks mined |
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| `sleep_schedule` | install a nightly cron entry (`--hour` / `--minute`) |
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| `sleep_unschedule` | remove the nightly cron entry |
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Default backend is `mock` (no API spend); the `claude`, `codex`, and `copilot`
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backends use the corresponding authenticated CLI and budget. The seven tools
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call the same `python -m skillopt_sleep` actions as the other shared-engine
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integrations.
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## Data boundary
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The Devin harvester reads local ATIF transcripts, agentmemory, and skill files
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and converts them into the engine's session format. The `mock` backend keeps
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that workflow local. A real backend sends truncated excerpts and derived tasks
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to the selected provider for mining, replay, judging, and reflection. The
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conversion step is not a guarantee that outbound prompts contain no secrets;
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review sensitive sources and provider policy before enabling a real backend.
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See the [shared data-boundary guidance](../README.md#data-boundary) and
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[implemented CLI reference](../README.md#supported-cli-surface).
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