dsh-evolution-lab
DeepSeek Harness 的携带证明技能自我进化。
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add dsh-evolution-lab@0.3.1Evolution Lab 以 dsh-evolution-lab 发布，当前版本为 0.3.1。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
Proof-carrying Skill self-evolution for DeepSeek Harness. Evolution Lab turns repeated project experience into quarantined SKILL.md candidates, evaluates baseline and candidate in isolated DSH processes, runs held-out canaries, and atomically promotes or rolls back without a manual approval queue.
The autonomy boundary is deliberately narrow: V1 evolves one Markdown Skill at a time. It cannot generate Cordis plugins, scripts, tools, workflows, presets, sandbox rules, approval policy, DSH configuration, or DSH source changes.
| Evolution Lab | DSH | Node.js | Profiles |
|---|---|---|---|
| 0.3.x | 0.1.0-rc.6 | Node.js 22 / 24 | web, headless |
DSH is in developer preview. Every supported DSH release must pass a real packed-profile smoke test before this matrix expands.
Install into every profile that should host the controller. The npm package is the default public path:
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add dsh-evolution-lab@0.3.1
The GitHub Release publishes the same build with a SHA-256 checksum, for installations that prefer pinning a verified remote archive. Both paths pass clean web/headless profile smoke tests before release:
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add https://github.com/JayDong9130/dsh-evolution-lab/releases/download/v0.3.1/dsh-evolution-lab-0.3.1.tgz
Install a pinned GitHub revision:
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add github:JayDong9130/dsh-evolution-lab#<commit-sha>
Git-hosted packages run their prepare script, so pnpm intentionally blocks the first source install unless the exact archive is trusted. Copy the complete key printed by ERR_PNPM_GIT_DEP_PREPARE_NOT_ALLOWED into $DSH_HOME/profiles/web/pnpm-workspace.yaml, then rerun the command. For a commit install it has this shape:
allowBuilds:
dsh-evolution-lab@https://codeload.github.com/JayDong9130/dsh-evolution-lab/tar.gz/<commit-sha>: true
Keep the full package-plus-URL key; do not replace it with a broad wildcard. Repeat the same profile-local step for headless when installing source there. npm and Release tarball installs use prebuilt lib/ and do not need this Git-source exception.
Alternatively, install a previously downloaded and SHA-256-verified Release tarball:
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add ./dsh-evolution-lab-0.3.1.tgz
Verify that the composed profile contains the dsh-evolution-lab bundle layer and id: evolution-lab:
npx @deepseek-ai/dsh@0.1.0-rc.6 --profile web --dump-config
The plugin is installed per profile. Repeat the command for headless only when that profile should observe sessions; evaluator subprocesses use a controller-disabled profile and never evolve themselves.
After installing or upgrading, restart DSH Web and refresh the page. Open a conversation whose session belongs to the Git project you want to evolve. The compact Enable auto evolution control appears in the current conversation header through DSH's additive conversation.session.header.actions slot. Click it once; Evolution Lab atomically creates .dsh/evolution/config.yaml with safe defaults and enables that project. The same control then reports and changes the current project's state.
The browser sends only the current sessionId. The Host resolves the authoritative session working directory and Git root; it never accepts a browser-supplied path. The control is disabled outside a Git project. If an existing config is invalid, it reports Invalid config and refuses to overwrite it.
Without .dsh/evolution/config.yaml, Evolution Lab is observe-only and performs no model calls or project mutations. Headless users, or users who want to review every setting before enabling, can create the file manually:
version: 1
enabled: true
engine:
kind: native
provider: deepseek
model: deepseek-chat
collection:
includeSubagents: false
maxTrajectoryBytes: 131072
minClusterSize: 3
minEvidenceWeight: 20
evaluation:
minTasks: 3
maxParallel: 2
timeoutMs: 600000
requiredPassRateDelta: 0.05
maxCostRatio: 1.20
maxDurationRatio: 1.50
canary:
minTasks: 2
requiredPassRateDelta: 0
promotion:
automatic: true
monitorIntervalMs: 86400000
rollbackAfterConsecutiveFailures: 2
Nothing is ever promoted without frozen, deterministic tasks under .dsh/evolution/evals/<task-id>/. A project with too few tasks is not blocked with an error — it simply collects trajectories forever and never promotes. Run /evolution eval init to write a runnable starter pack plus a README describing the task contract, then check what is still missing:
/evolution status
The evals section reports the tasks found per split against the configured evaluation.minTasks and canary.minTasks, lists blockers such as INSUFFICIENT_CANARY_TASKS, and names any task directory that failed to load.
The starter pack is one validation and one canary task exercising a toy string helper. It proves the pipeline runs; it does not evaluate your project. Replace it with tasks drawn from real failures in this repository — a candidate that only beats the baseline on the examples has proven nothing. Keep canary tasks genuinely held out: the proposer never sees or edits them. See the architecture for the full task contract.
Arena starts a clean headless DSH profile and passes only an explicit environment allowlist. If the evaluator model authenticates through an environment variable, configure the plugin row in the profile or home cordis.patch.yml; values are read from the launch environment and are not written into the patch:
- id: evolution-lab
config:
evaluator:
allowedEnv: [PATH, DEEPSEEK_API_KEY]
The default evaluator command reuses the current DSH 0.1.0-rc.6 CLI with --profile headless. Advanced installations may set evaluator.command and evaluator.args. The child sets DSH_EVOLUTION_CONTROLLER_DISABLED=1, so an evaluator profile fails closed against recursive evolution.
/evolution status — configuration, active versions, queue, evaluation readiness, proof and monitor health./evolution run — enqueue a cycle; it cannot skip evidence or safety gates./evolution eval init — scaffold a runnable starter task pack under .dsh/evolution/evals/. It never overwrites an existing file./evolution history [skill] — immutable candidate, promotion and rollback records./evolution rollback <skill> — restore the newest proven predecessor./evolution enable / /evolution disable — change the local enabled flag.The model receives one read-only evolution_status tool. It cannot choose a winner, promote a candidate, weaken policy, or grant an exception.
committed session events
-> local two-pass redaction
-> intent atoms and evidence-weighted clusters
-> quarantined Skill candidate
-> immutable safety scan
-> isolated baseline/candidate validation
-> held-out deterministic canary
-> proof written before atomic activation
-> scheduled probes
-> automatic rollback on regression
No manual approval means there is no pending-approval queue. It does not mean unrestricted modification. Unsafe, under-evaluated, stale, privacy-failing, or regressing candidates are rejected automatically; there is no override flag.
Raw DSH session logs remain DSH-owned. Evolution Lab stores bounded, redacted envelopes under .dsh/evolution, with HMAC pseudonyms for sensitive identifiers and a second leak scan before persistence or engine submission. The 256-bit HMAC key is stored with mode 0600 under $DSH_HOME/evolution-lab, never in the project. It never submits raw events, absolute home paths, credentials, canary fixtures or proof files to the native model or optional xskill bridge.
Default retention is 30 days for redacted trajectories, 90 days for run reports, and indefinite for the proofs/version lineage needed to validate or roll back an active Skill. To delete learned data, first run /evolution disable, keep or restore any desired .dsh/skills mirror, then delete the project's .dsh/evolution directory. Deleting version/proof data removes rollback history.
There is no telemetry. Network access is used only by the configured DSH model provider, an explicitly configured xskill bridge, package installation, or evaluation tasks whose execution policy permits it. Native proposal calls and baseline/candidate runs consume model tokens; Arena subprocesses also consume CPU and wall-clock time. Use the configured cost, duration and concurrency limits.
The immutable policy allows exactly one regular SKILL.md up to 16 KiB with fixed invocation policy. Evaluation uses separate workspaces, DSH homes, agent homes, sessions, bounded output and explicit environment allowlists. The plugin-owned SkillProvider invalidates immediately after promotion/rollback; .dsh/skills is a portable mirror, not the consistency mechanism.
Read SECURITY.md and the security model before enabling automatic promotion in a sensitive repository.
Disable evolution first and decide whether to keep promoted project Skills. Then remove the bundle:
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web remove dsh-evolution-lab
Uninstalling does not delete .dsh/evolution or .dsh/skills; delete them explicitly only after reviewing the rollback implications.
npm install
npm run verify
The implementation is DSH-native TypeScript. It credits xskill's MIT-licensed atom/cluster/version/canary vocabulary as design inspiration but copies no xskill source and has no Python or xskill runtime dependency.
License: MIT.