dsh-find-skill

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Bridge the vercel-labs/skills open agent-skills ecosystem into DeepSeek Harness (dsh).

The plugin lets the LLM decide when a task needs a skill no existing tool or loaded skill covers: the model searches the ecosystem (skill_find), asks the user which candidate and scope to install (ask_user_question, built into dsh), and loads it as temp (default, current session), project (shared with the workspace), or global (all sessions). Installs land in plugin-owned roots, isolated from hand-written .dsh/skills and shared .agents/skills.

Features

• skill_find — remote search over the official skills.sh API (the same source the CLI find command queries). Candidates carry install counts, sources, browse URLs, and a local "installed" marker. Low-priority description: the model is told to use it only when no existing tool or loaded skill fits.
• skill_install — fetch through the official CLI (npx -y skills@latest, auto-latest per project decision) inside an isolated throwaway work/home pair, then adopt only the requested skill into a managed scope. Temp installs register as runtime skills; project/global installs are written to managed roots and exposed through a self-owned ctx.skills provider (rank 350, configurable).
• skill_remove — remove from temp / project / global; temp is tried first when no scope is given.
• /skill command — human-facing find | install | update | sync | remove | list; update re-fetches the recorded source and replaces the bundle; sync scans project node_modules skills via the official CLI's experimental_sync and adopts them into the managed root.
• Lifecycle — temp skills register through the installing agent's scoped context: visible only to that session (other sessions cannot read them), the registration unwinds when the agent/session is disposed, and materialized directories are cleaned on session/disposed; compactDisposePolicy: keep | dispose | ask controls compaction behavior.
• Web UI cards — the dsh-find-skill-client package renders dedicated, replayable, read-only conversation cards for skill_find / skill_install / skill_remove tool calls.; compactDisposePolicy: keep | dispose controls behavior at compaction.

Install / Load

From source

git clone https://github.com/Moximxxx/dsh-find-skill.git
cd dsh-find-skill
git checkout develop          # full develop branch (includes AGENTS.md, .dsh/)
pnpm install --config.minimumReleaseAge=0   # rc.6 packages need the release-age policy bypass
pnpm build                    # tsc → lib/
pnpm test                     # unit + snapshot tests

Load it into dsh — development overlay (hot source):

- insert:
    - id: dsh-find-skill
      name: '/abs/path/to/dsh-find-skill/src/index.ts'

Or install the local checkout as a bundle (build first, then):

dsh plugin --profile web add /abs/path/to/dsh-find-skill
dsh --profile web --dump-config   # confirm the dsh-find-skill row is in the plugin tree

From npm

dsh plugin --profile web add dsh-find-skill

Published to npm; install directly.

Configuration

All fields are optional; defaults shown.

Usage flow (model-driven)

1. User asks for something; the model finds no existing tool or loaded skill fits.
2. Model calls skill_find → reviews candidates (installs, source, URL).
3. Model asks the user via the built-in ask_user_question (which candidate? temp/project/global?).
4. Model calls skill_install → the skill appears in the session skill catalog on the next step; load it with the skill tool or the user can type /<skill-name>.
5. Cleanup: temp skills disappear at session end or via skill_remove; project/global persist until removed.

Model Experience

• The three tools are registered with low-priority descriptions and can be disabled per tool; catalog noise is bounded by searchLimit and by installing only selected skills.
• Tool calls and results flow through the standard tool/call / tool/result session events; nothing is injected outside the session log.
• CLI installs can take tens of seconds on first use (npx downloads the latest skills package into the shared npm cache; the fetch itself runs in a throwaway HOME so no agent directories are touched).
• Project/global skills are durable files; temp skills are in-memory registrations with materialized directories under tempSkillRoot.

Known Limitations and Deferred Work

• Search candidates carry no description: the skills.sh search API returns id/name/installs/source only; descriptions arrive after install.
• Version compatibility: development and loading tests target npm @deepseek-ai/*@0.1.0-rc.6; the source checkout (rc.5) was verified in an isolated instance (probe-confirmed apply execution and healthy boot).
• CLI stdout is advisory: outcomes are judged from the filesystem (the adopted skill directory), never from CLI prose.
• Real-session model-driven flow verified (headless with a real model: skill_find → skill_install temp → skill load); the full loop passed, including temp-skill session isolation (visible to the installing agent, invisible to a subagent).
• node_modules-synced skills have no remote source: update is unavailable for /skill sync adoptions; re-sync or install manually.
• Web cards are read-only: no install/remove buttons yet; labels are fixed English, i18n deferred.

License

MIT