✨ Highlights

Built for DeepSeek Harness, DSH Knowledge Forge turns Agent conversation traces into progressively reusable knowledge.

• A first durable task case becomes a human-readable Wiki page.
• A later independent case that repeats the same stable workflow can promote that Wiki into a native DSH Skill.
• The Wiki then becomes compact metadata pointing to the Skill, so the Agent discovers procedures progressively instead of placing every Skill in the prompt.

Overview

DeepSeek Harness is a plugin-first open-source Agent Harness. DSH Knowledge Forge is a native DeepSeek Harness plugin that adds automatic local knowledge distillation without requiring an external memory service.

Agent sessions contain valuable engineering memory: what was attempted, what users corrected, what evidence mattered, which decision worked, and where a blocked task should resume. Raw transcripts are too large and noisy to become long-term context, while a single lossy summary is too hard to audit.

Knowledge Forge separates operational evidence from reusable knowledge:

• SQLite keeps queue state, scheduling, retries, receipts, Case relationships, and full-text indexes.
• Markdown keeps the durable Wiki and Skill artifacts readable and editable.
• A compact Wiki index guides recall without injecting every knowledge page or Skill into the prompt.

The result is a local knowledge loop for DeepSeek Harness:

work happens -> valuable Case becomes Wiki -> repeated workflow becomes Skill -> future sessions reuse it

How it works

1. Capture completed top-level turns

The plugin listens to DSH's top-level turn lifecycle. It extracts user-visible messages, bounded assistant output, reduced tool evidence, and relevant paths. Reasoning traces and full tool output are not copied.

Before persistence, candidate text is:

• redacted for credential-like content;
• truncated to configured limits;
• isolated by Git workspace and source Session;
• assigned an idempotent event identifier.

2. Schedule each Session independently

A source Session becomes due when either condition is met:

• it has 5 pending turns; or
• its oldest pending turn has waited 60 minutes.

Due Sessions are evaluated separately. Turns from different Sessions are never combined into one model request.

3. Run a one-shot background curator

Knowledge Forge starts a DSH subagent with these constraints:

• exactly one non-interactive response;
• no tools;
• strict JSON output schema;
• every input event must receive one result;
• all candidate and knowledge text is treated as untrusted data.

The Host validates event coverage, Case membership, safe identifiers, promotion evidence, and credential-like output before writing any artifact.

4. Distill Wiki first, Skill when repetition proves reuse

The knowledge policy is deliberately progressive:

1. Discard lookups, casual questions, transient chatter, and unchanged reuse of an existing Skill.
2. Reuse an existing Skill when it already covers the task.
3. Write or update a Wiki for a durable task Case: objective, user feedback, evidence, decisions, outcome, blockers, and continuation points.
4. Promote to a Skill only when a new independent Case repeats the same stable, executable workflow with clear inputs, steps, and verification.
5. Replace the Wiki body with lightweight Meta that points to the generated Skill.

This design keeps memory useful without treating every conversation as knowledge or every repeated phrase as automation.

Quick start

Requirements

• Node.js ^22.19.0 || >=24.0.0
• DeepSeek Harness 0.1.0-rc.6

Knowledge Forge uses Node's built-in node:sqlite; no separate SQLite installation is required.

Install from this repository

Clone and build a prebuilt tarball:

git clone https://github.com/bill084153-cell/dsh-knowledge-forge.git
cd dsh-knowledge-forge
npm install
npm run build
npm pack

Install it into the DSH Web profile and start DSH:

dsh plugin --profile web add ./dsh-knowledge-forge-0.1.0.tgz
dsh web

The tarball path can be absolute. Install the bundle into every DSH profile where automatic knowledge capture should run. The Web profile additionally exposes the Dashboard.

Direct GitHub installation of a TypeScript DSH plugin requires an install-time build allowance. Building a tarball first keeps installation explicit and avoids running repository build scripts inside the user's DSH profile.

Verify installation

dsh web --dump-config | grep -A 8 dsh-knowledge-forge

dsh plugin --profile web exec \
  dsh-knowledge-forge doctor --workspace .

Expected doctor output includes the workspace root, local database path, queue counts, Wiki count, Skill count, and status: ok.

Storage layout

Knowledge Forge writes only inside the current project:

<project>/.dsh/
├── knowledge-forge/
│   ├── knowledge-forge.sqlite     # queue, batches, receipts, retries, FTS index
│   └── wiki/
│       ├── index.md               # compact recall map injected into Agent context
│       └── pages/
│           └── <wiki-id>.md       # durable task Cases or Skill metadata
└── skills/
    └── <skill-id>/
        └── SKILL.md               # native DSH Skill discovered by the Skill catalog

SQLite is operational state. Markdown Wiki pages and SKILL.md files are the readable long-term artifacts.

Trigger, retry, and retention

A long-running dsh web process can honor the age timer precisely. If DSH is stopped, pending work remains in SQLite and catches up when the workspace is active again.

The scheduler is process-level, not one permanent process per Session. If the exact source Agent is no longer live, another live top-level Agent in the same workspace may host the one-shot worker. Otherwise the batch waits for the next workspace activity.

Dashboard and operations

Install the plugin in the Web profile, run dsh web, then open Settings → Knowledge Forge.

The Dashboard shows:

• Workspace and source Session filters;
• pending, running, waiting, completed, and dead-letter counts;
• source Session and worker Session navigation;
• batch trigger reason and per-turn action;
• generated Cases, Wiki pages, and Skills;
• validation or execution errors.

In-session commands

/knowledge-forge
/knowledge-forge run
/knowledge-forge retry <batch-id|all>

Offline diagnostics

These commands read local state and do not start a model:

dsh plugin --profile web exec \
  dsh-knowledge-forge status --workspace .

dsh plugin --profile web exec \
  dsh-knowledge-forge doctor --workspace .

Knowledge recall

Knowledge Forge adds two read-only tools:

At Agent creation, the plugin injects only the compact Wiki index. Full pages and Skill bodies are loaded on demand. This follows DSH's native Skill model and preserves context space.

Architecture

The plugin has no external service dependency. Its runtime stays inside the DSH process and the current project directory.

Security and privacy

• Raw Session logs, model reasoning, full tool output, and secrets are not copied into the plugin database.
• Candidate text is redacted and bounded before persistence.
• Candidate, Wiki, Skill, path, tool argument, and tool output text is untrusted input.
• The background Agent receives no tools and cannot execute candidate instructions.
• Host validation runs before every Wiki or Skill write.
• Artifact identifiers are restricted to safe kebab-case paths.
• Writes use atomic file replacement inside declared project roots.
• The Dashboard endpoint is read-only and follows the existing DSH Web exposure boundary.
• Operational rows expire after 90 days; curated Wiki and Skill artifacts remain until a user edits or removes them.

Configuration

The shipped bundle defaults are defined in cordis.patch.yml:

- insert:
    - id: knowledge-forge
      name: dsh-knowledge-forge
      config:
        turnThreshold: 5
        maxAgeMinutes: 60
        retentionDays: 90
        maxRetries: 3

A later DSH profile patch can override the plugin row. Available options also include processingLeaseMinutes, candidate and tool preview limits, Wiki context size, and enabled.

Development

npm install
npm run typecheck
npm test
npm run build
npm run pack:check

The current suite covers candidate extraction, redaction, scheduling and Session isolation, retry/dead-letter behavior, structured-output validation, atomic Wiki/Skill writing, native DSH Skill discovery, bundle composition, and Dashboard transport behavior.

Project status

Knowledge Forge currently targets DeepSeek Harness 0.1.0-rc.6, which is a developer-preview release. DSH APIs may change before a stable release; compatibility updates may be required.

Contributing

Issues, documentation improvements, compatibility fixes, and new tests are welcome. Please keep contributions scoped to the automatic local knowledge-distillation plugin and avoid introducing framework-specific business integrations into the core.

If this project is useful, consider starring the repository and sharing concrete Wiki/Skill promotion cases through GitHub Issues.

License

MIT © 2026 Zhongxibiao