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Plugin Write

Organization
oh-my-dsh
plugin-write

Use when creating a DeepSeek Harness plugin, choosing public names for a new external DSH plugin, validating a dsh-plugin.naming.json manifest, checking reviewed central registrations for known conflicts, or creating a workspace package inside the deepseek-harness repository. Covers the full workflow from repository-mode and plugin-form selection through separate offline naming validation, optional online registry lookup, and package validation. Routes tool, LLM adapter, hook, service, and configuration forms to their corresponding references while separating upstream-monorepo rules from external-package rules. For an existing plugin crossing Harness versions, use this Skill's built-in version-adaptation workflow before implementing against the exact target contract.

Overview

Publisheroh-my-dsh
Repositorydsh-plugin-upgrade-skill
Skill nameplugin-write
Stars
300
Forks
36
Bundled files
14
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oh-my-dsh on GitHub. Read the source before you install it.

Installation

Install the Plugin Write AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/oh-my-dsh/dsh-plugin-upgrade-skill/tree/main/skills/plugin-write
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/oh-my-dsh/dsh-plugin-upgrade-skill.git /tmp/dsh-plugin-upgrade-skill
mkdir -p .claude/skills
cp -r /tmp/dsh-plugin-upgrade-skill/skills/plugin-write .claude/skills/plugin-write
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plugin Write in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Plugin Write on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Plugin Write is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Write DeepSeek Harness Plugins

Create a plugin package. First classify the repository mode and plugin form, then read the matching reference files, and finally validate the published entry with the smallest set of gates that covers the change.

Select the Repository Mode First

TargetRules to apply
A package inside the official deepseek-harness monorepoUse the in-repository package, tsconfig, documentation, and root-gate rules below.
An externally installable DSH pluginPreserve that repository's package layout and scripts. Use only packages and exports published by the exact target DSH version. Do not copy private, workspace versions, root tsconfig registration, or monorepo-only README gates.
An existing plugin being adapted to a new DSH hostRead references/version-adaptation.md, build the complete version corridor, and run the seven-class touchpoint preflight. If a change is breaking and the user has not yet authorized implementation, present the migration plan and wait for confirmation. After authorization, complete the version adaptation before using this Skill's form references. Form examples must never override target source, type declarations, or release notes.

Derive Cordis, Schemastery, and DSH package names and version ranges from the manifest of the exact target version. Current examples use scoped @deepseek-ai/* identifiers. Older targets may differ and must follow their own published contracts.

For every new external plugin, read references/naming-conventions.md before choosing public identifiers. Create dsh-plugin.naming.json at the plugin repository root and run the bundled read-only validator before final package validation. Treat compatibility errors as target-contract failures and prefix warnings as community recommendations; use --strict only when the plugin adopts the collision-resistant profile. This is not an official Harness manifest or a global reservation. For an existing external plugin, report naming deviations but preserve published names unless the user explicitly authorizes a compatibility-breaking rename. Packages inside the official monorepo follow the exact target checkout instead of this external naming profile.

After the offline declaration passes, read references/registry-check.md and run the separate central lookup when public network access is available. Supply the exact target Harness version and preserve the reported index SHA-256 with the source URL as evidence. Treat a completed no-match result only as “no reviewed match”; treat timeout, malformed data, unsupported contract, oversized input, or network failure as “unknown/not checked.” Never let the online lookup modify the local manifest, automatically rename a published surface, or turn an automated discovery candidate into a reservation. When central registration is explicitly selected, prepare the full v2 entry and run the central repository's check and verify-source commands before copying it into registry/entries. Validation does not authorize submitting a PR; a formal reservation exists only after a source-backed entry is reviewed and merged in the central registry.

Then Classify the Plugin Form

Required capabilityFormReference
Model-callable tools for reading files, running commands, or searching the WebTool pluginreferences/tool-plugin.md
A new model providerLLM adapter pluginreferences/llm-adapter-plugin.md
Request, tool, or turn interception for permissions, policy, metrics, or telemetryHook pluginreferences/hook-plugin.md
A capability consumed by other plugins through ctxService pluginreferences/service-plugin.md
User-configurable behavior supplied through cordis.ymlConfig pluginreferences/config-plugin.md

A plugin may combine forms freely, such as a configurable tool plugin or a service that also registers tools. Every included form still has to satisfy its own contract. When a requirement does not match one of the five forms above, map it to an existing extension point and write a plugin that registers there. Never modify the Agent loop directly.

GoalMechanism
Add a model-callable capabilityRegister it on ctx.tools
Add a model providerRegister an adapter on ctx.llm
Provide a different capability set for one sessionAssemble it in an Agent preset
Add Shell executionImplement and register a ctx.bash backend
Add persistent terminal executionRegister a ctx.pty backend and load dsh-tool-pty
Add human commandsRegister them on ctx.commands
Add background tasksRegister them on ctx.tasks
Add filesystem access or policyImplement a ctx.fs provider or listen for fs/* policy events
Constrain launched processesUse a ctx.sandbox backend
Intercept requests, tools, or turnsUse agent/* or tools/* events; agent/turn-stopping is the turn-stopping event
Add model-visible contextCall agent.inject()
Add UI or editor integrationDrive ctx.agents and render from session/event
Add Web-client conversation nodesRegister a ConversationNodeDefinition and keyed renderers
Add persistent session stateExtend SessionEventMap, then render and replay from the log
Fork a live sessionCall ctx.sessions.fork(source, boundary?, childSessionId?)
Scope registrations to one AgentUse that Agent's agent.ctx

Package Checklist

  1. Create an in-repository package — Only in the official monorepo, create packages/<group>/<pkg>/ with package.json, tsconfig.json, src/index.ts, and README.md. Copy packages/core/tools/package.json from the target checkout, then adjust its name, description, and dependencies. Preserve target-version invariants: private: true; the root package version; type: module; main: "lib/index.js"; types: "lib/types/index.d.ts"; both types and default in exports["."] pointing to lib; the same target Cordis range in peer and development dependencies; every DSH peer dependency mirrored in development dependencies; the target Schemastery package declared in dependencies; and the target files layout plus package-specific runtime artifacts. CLI application packages must include the built bin. Do not publish undeclared source or stale artifacts. Follow relative-import conventions from the target checkout. Prefer an existing group with the matching role. A new group is only a container, and the package must sit exactly one level below it.

  2. Register an in-repository package — Only in the official monorepo, add the package to the Host or Client aggregate exactly as required by the development guide in the target checkout. A normal package belongs to one aggregate only. Do not copy historical exceptions or file lists without checking the target version. External plugins must never modify Harness root configuration.

  3. Create an external package — Preserve the existing package manager and build system. For a new plugin, apply the external naming policy and include a validated dsh-plugin.naming.json; for an existing plugin, do not silently rename public surfaces. Keep main, types, exports, files, optional bin, packaged-composition or Profile metadata, and the packed tarball consistent. Declare every runtime dependency explicitly and mirror the DSH peer dependencies needed for compilation in development dependencies. Do not make a publishable external plugin private or give it workspace version ranges merely because an in-repository template does so.

  4. Choose the package topology — For a replaceable capability, split service definition, provider, and consumer into separate packages only when they will evolve independently. Keep a single-purpose plugin in one package.

  5. Write the in-repository package README — Only when required by the target monorepo, put package-specific service APIs, configuration, events, extension points, and design notes first. End the README with the canonical "Model Experience" ordering and "Known Limitations" section from the target checkout. Describe each direct, conditional, capped, lifecycle, or auxiliary-model surface in its own H3 with the following three H4 sections, each containing a prose paragraph. Quote stable text owned by the package. For a tool Schema surface, describe only differences not already present in the generated tool catalog. Under "KV Cache Impact," distinguish append-only growth, stable repeated prefixes, replacement of earlier request tokens, and independent model requests. Then list the package changes that invalidate reuse.

    markdown
    ## Model Experience
    
    ### Request Surface and Activation Conditions
    
    #### What the Model Sees
    
    Name the exact data-dependent field, link to the generated catalog with an anchor, or introduce the verbatim text below.
    
    ##### Place the Verbatim Field Text Here When Needed
    
    ```markdown
    Copy any stable system-prompt body or other long nongenerated literal exactly from source.
    ```
    
    #### Token Impact
    
    State whether the impact is fixed, conditional, retained, replaced, capped, or has zero direct token impact.
    
    #### KV Cache Impact
    
    Describe append-only, prefix-stable, replacement, or independent behavior, including exact conditions that may invalidate reuse.
    
    ## Known Limitations and Deferred Work
    
    - **Consumer-visible gap** — State the exact missing operation or condition, its consequence, and any maintainer constraint.
  6. Validate — For a new external plugin, first run node <plugin-write-skill>/scripts/validate-names.mjs --manifest ./dsh-plugin.naming.json; add --strict only for the collision-resistant community profile. After it passes, run node <plugin-write-skill>/scripts/query-registry.mjs --manifest ./dsh-plugin.naming.json --harness-version <exact-semver> when network access is available, and report an unavailable query as unknown rather than available. If proxy variables are present and Node's built-in fetch cannot reach the index, follow references/registry-check.md; do not imply that Node 20-23 automatically honor those variables. Then run the applicable validation block below, focused checks, and coverage gate required by the changed behavior.

Rules While Writing

  • Treat every registration as an effect. Register through ctx helpers or ctx.effect() with a disposer, and make plugin unload clean up every event listener, tool, timer, and other resource.
  • Add new behavior at documented extension points. Do not modify agent-loop.
  • Give public service methods and typed events JSDoc with @param and @returns. Define typed events through declaration merging on the target Cordis Events interface, and document the dispatch mode with @mode.
  • Do not hard-code tunable values. Any value that may differ across deployments must be a validated Config field changeable through cordis.yml.
  • Everything the model sees must be reconstructible from the session log.
  • Fail explicitly on configuration errors. Never silently skip a missing referenced object. Validate at parser, configuration, wiring, and process boundaries instead of trusting an in-process typed caller.

Validation

For packages inside the official Harness monorepo, use current root commands from the target checkout. The names below are examples only; confirm they exist before running them:

sh
pnpm install            # Register the workspace
pnpm run doc-sync
pnpm run constraints && pnpm run typecheck && pnpm run lint
pnpm run build && pnpm run hygiene

For an external plugin, use its own install, typecheck, test, static-check, and build commands. Pack the publishable artifact, inspect its contents, and load it into an isolated Profile running the exact target DSH. For an upgrade, cold-start it and complete one message → tool → reply flow or an equivalent core flow. Report every provider, operating-system, UI, or credential boundary that remains uncovered.

Select tests from the changed surface: unit-test logic; run the repository's coverage gate; run real-API end-to-end tests when provider credentials are available and execution is authorized; use credential-free snapshots for model-, protocol-, or user-visible behavior; and use a real-composition test for user-visible plugins. A package bin entry also needs a built-artifact smoke test under native Node. Complete the minimum sufficient test set under these rules without loading another Skill.

See references/README.md for the reference index.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Plugin Write AI skill do?

Use when creating a DeepSeek Harness plugin, choosing public names for a new external DSH plugin, validating a dsh-plugin.naming.json manifest, checking reviewed central registrations for known conflicts, or creating a workspace package inside the deepseek-harness repository. Covers the full workflow from repository-mode and plugin-form selection through separate offline naming validation, optional online registry lookup, and package validation. Routes tool, LLM adapter, hook, service, and configuration forms to their corresponding references while separating upstream-monorepo rules from ex...

Why use Plugin Write on TypingMind?

Because you install it once and use it with any model. Plugin Write is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Plugin Write in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oh-my-dsh/dsh-plugin-upgrade-skill/tree/main/skills/plugin-write. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Plugin Write?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Plugin Write?

As many as you like. As long as a model supports skills, you can use Plugin Write with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Plugin Write AI skill free?

Yes. It is published on GitHub by oh-my-dsh under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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