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khashayar bec23ed020 Add Devin plugin (plugins/devin): MCP server + ATIF-v1.7 harvest

Wires the skillopt_sleep engine into Devin (Cognition) via an MCP server,
following the same thin-shell pattern as plugins/copilot.

- mcp_server.py: stdlib-only stdio MCP server exposing the standard sleep_*
  tools (status, dry-run, run, adopt, harvest). REPO_ROOT defaults to ../.. so
  it finds skillopt_sleep automatically when run from plugins/devin/.
- harvest_devin.py: converts Devin ATIF-v1.7 transcripts, agentmemory, and
  .devin/skills/*/SKILL.md into the Claude Code-compatible JSONL the engine
  consumes; enriches with taskKey + outcome envelopes (hard test/build signal
  or judge rubric). Workspace auto-detection; cross-platform paths.
- judge.py, mcp-config.example.json, devin-rules.snippet.md, README.md.
- plugins/README.md: add Devin to the platform + install tables.

No changes to skillopt_sleep; shells out to `python -m skillopt_sleep` like the
other plugins. Pure stdlib; default backend mock (no API spend).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

2026-06-25 10:42:52 +02:00

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SkillOpt-Sleep (Devin)

You have access to a nightly self-evolution cycle via the skillopt-sleep MCP server. Use these tools to improve your long-term skills over time:

sleep_status — how many nights have run + the latest staged proposal
sleep_dry_run — preview a cycle without changing anything
sleep_run — run a full cycle; stages a proposal for review
sleep_adopt — apply the staged proposal to .devin/skills/skillopt-sleep-learned/SKILL.md
sleep_harvest — debug: list the recurring tasks mined from recent sessions

When a user asks about the sleep cycle, skill evolution, or improving your long-term memory, prefer calling these tools over explaining the concept.

Default backend is mock (no API spend). Pass backend: "claude" or backend: "codex" with your own API key for real LLM-driven optimization.

Place this file at .devin/rules/skillopt-sleep.md in your workspace.

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SkillOpt-Sleep (Devin)

944 B

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