Build DeepSeek Harness Plugins with a Standardized Agent Skill

Where this fits

You're a developer extending DeepSeek Harness (DSH) with a custom model adapter or a new tool registry. The official docs scatter conventions across tutorials, reference pages, and generated project skeletons—so your agent often guesses at plugin structure, config keys, and test patterns. This skill encodes those conventions into a single, executable standard. Any agent that loads it can scaffold, implement, and evaluate DSH plugins the same way, cutting down on trial-and-error and review cycles.

Why agents benefit

• Enforces 8 hard rules from the skill's SKILL.md, so the agent won't produce plugins that violate DSH's plugin lifecycle or config schema.
• Loads 12 reference documents on demand via progressive disclosure—the agent fetches only the standards relevant to the current task (e.g., tool registration vs. session logging), keeping context small.
• Runs 6 scenario workflows covering common tasks like adding a model adapter, wiring a custom agent loop, or writing a session logger—each with step-by-step instructions and completion checklists.
• Generates evals alongside code, so the agent can verify plugin behavior against DSH's harness before you commit.
• Provides a decision quick-reference for ambiguous choices (e.g., when to use a service vs. a middleware), reducing back-and-forth between you and the agent.

Practical scenarios

Adding a custom model adapter

You need to plug in a local LLM endpoint that DSH doesn't support out of the box. The agent loads the adapter reference, scaffolds the plugin structure, implements the required interface, and writes a small eval that mocks the endpoint—so you can test the adapter without spinning up the full harness.

Replacing the default agent loop

Your team wants a custom turn-taking policy. The agent consults the agent-loop standard, generates a plugin that overrides the loop's core hooks, and validates it against the provided eval harness. You get a drop-in replacement that follows DSH's extension points.

Extending the tool registry with domain-specific tools

You're building a research agent that needs a database query tool. The agent uses the tool registration workflow to create a plugin with proper input schemas, error handling, and a test that verifies tool invocation through the harness's registry.

Add it to your agent workflow

Install the skill with:

npx skills add zimodzh/dsh-plugin-dev-skills

Then ask your agent to "create a DSH plugin for a Slack tool using the dsh-plugin-dev skill." The agent will load SKILL.md, follow the tool-registration workflow, and produce a plugin plus an eval file—ready for you to review and commit. For a full overview, see the skill listing on OpenAgentSkill.

Compare before adopting

Before adding this skill to your standard stack, compare it against:

• Quality signals: Does the repo have recent commits and a clear license? The README shows MIT, last-commit badges, and Agent Skills compliance—good signs.
• Maintenance freshness: Check the GitHub repo for active issue responses and version bumps. Community-maintained skills can drift from official docs.
• Alternatives: If you only need one-off plugin code, a generic coding agent prompt might suffice. This skill shines when you have multiple plugins or want consistent evals.
• Workflow fit: If your agent already has a custom DSH plugin template, weigh the overhead of adopting this skill's conventions vs. the benefit of standardization.

Why it is worth tracking

With 34 stars and an active last-commit badge, this skill shows early community traction. It's the first to codify DSH plugin development into an agent-readable format, and its structured standards + eval approach aligns with best practices for agent skills. Track it if you build on DeepSeek Harness or want a template for creating similar domain-specific skills. Re-evaluate after the next DSH release to see if the skill stays current.