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dsh-skillopt

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Nightly self-improvement for your DeepSeek Harness agent: harvest past sessions, replay recurring tasks, and consolidate validated skills behind a held-out gate. Brings microsoft/SkillOpt's SkillOpt-S

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SkillOpt-Sleep — DeepSeek Harness (dsh) integration

Give your DeepSeek Harness agent a nightly sleep cycle: it reviews past sessions offline, replays your recurring tasks on your own API budget, and consolidates what it learns into validated skills behind a held-out gate. Same engine as the Claude Code / Codex / Cursor integrations (skillopt_sleep), wired into dsh's plugin system as native tools plus a bundled skill.

DeepSeek Harness is the "everything is a plugin" agent framework (deepseek-ai/deepseek-harness). Plugins are TypeScript modules exporting an apply(ctx) function that register capabilities (tools, services, events, settings) on the Cordis context.

Why a sleep cycle?

Skills improve when an agent re-examines its own sessions — not just when you hand-tune a prompt. The sleep cycle turns your everyday usage into a nightly, validation-gated skill-improvement loop: harvest what you actually did, replay the recurring tasks on your own API budget, and keep only the changes that pass a held-out gate. It's the same engine as the Claude Code / Codex / Cursor integrations, wired into dsh as native tools plus a bundled skill.

What this integration adds

| Component | Purpose | |---|---| | src/index.js | dsh plugin entry: registers 7 skillopt_* tools + Schemastery config | | cordis.patch.yml | bundle patch layer — drop dsh-skillopt into any profile's bundles | | skills/skillopt-sleep/SKILL.md | agent skill: when to use the tools, operating rules, data-boundary rules | | scripts/sleep.py | bootstrap/self-check runner (same command shape the tools use) | | package.json | npm package metadata (bundle manifest) |

Tools

| Tool | skillopt_sleep action | Behavior | |---|---|---| | skillopt_status | status | state, engine availability, latest staged proposal & report | | skillopt_dry_run | dry-run | full preview (harvest+mine+replay), stages nothing | | skillopt_run | run | full cycle, stages a proposal (live files unchanged) | | skillopt_adopt | adopt | apply latest staged proposal (with backup) — the live-change boundary | | skillopt_harvest | harvest | read-only show/export of mined tasks | | skillopt_schedule / skillopt_unschedule | schedule / unschedule | install/remove the nightly cron entry |

Prerequisites

  • DeepSeek Harness (dsh) installed
  • Python 3.10+ with the SkillOpt-Sleep engine:
pip install skillopt          # or use this source checkout

Install

As a bundle in a profile

Add dsh-skillopt to the profile's bundles, or in the profile cordis.patch.yml:

- insert:
    - id: skillopt
      name: './src/index.js'
      config:
        backend: mock          # or codex / claude / cursor / pi / opencode / handoff …
        project: /path/to/project
        preferences: 'Always use async/await'

Local patch overlay (dev)

Run from a DeepSeek Harness source checkout (the official dev workflow, pnpm resolves the workspace dsh bin):

pnpm dsh web --patch ./plugins/dsh/cordis.patch.yml

If dsh is installed globally (npm install -g), use it directly:

dsh web --patch ./plugins/dsh/cordis.patch.yml

Either way the patch inserts the skillopt plugin row into the profile; then ask the agent: "Use skillopt_status to check the sleep cycle state."

Config keys

| Key | Default | Purpose | |---|---|---| | pythonCmd | python | Python interpreter for the engine | | module | — (bootstrap) | engine Python module override (python -m <module>) | | engineScript | — (scripts/sleep.py) | engine bootstrap script override | | project | — | default project directory | | scope | — | harvest scope: all | invoked | | backend | — | mock\|claude\|codex\|copilot\|cursor\|pi\|opencode\|handoff\|azure_openai | | source | — | claude\|codex\|copilot\|cursor\|pi\|opencode\|auto | | model | — | backend model override | | maxTasks / maxSessions | — | mine/harvest caps | | editBudget | — | bounded edits per cycle | | preferences | — | house rules for the reflection prior | | jsonOutput | false | machine-readable JSON output | | autoAdopt | false | OPERATOR-ONLY: auto-adopt a passed proposal without asking | | unscheduleAll | false | OPERATOR-ONLY: allow skillopt_unschedule to remove every managed entry | | timeoutMs | 600000 | per-call engine timeout in milliseconds |

Advanced engine keys (gate_mode, gate_metric, gate_no_regression, dream_rollouts, recall_k, evolve_memory/evolve_skill) go in ~/.skillopt-sleep/config.json — the same file shared by all integrations.

Data boundary

  • Harvest is read-only; mock/handoff make no network calls.
  • run stages proposals; adopt is the normal live-change boundary and backs up first.
  • Real backends send truncated transcript excerpts and derived tasks to the selected provider. For sensitive sessions, export tasks first (skillopt_harvest with output=), redact, set "reviewed": true, then replay — real backends refuse unreviewed task files.
  • Outbound prompts are not guaranteed secret-free; review source & provider policy.

Validate (no API spend)

python -m skillopt_sleep.experiments.run_experiment --persona researcher --assert-improves

See the SkillOpt-Sleep documentation for recorded results, limitations, and the supported integration surface.

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