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Specx Add Core Service

Community
maksimzayats
specx-add-core-service

Add or refactor a specx core scope service. Use when implementing focused reusable business/application behavior under a core scope services package, extracting logic from a use case, injecting deterministic collaborators, accepting an active unit of work, choosing between Service and Capability, or keeping business decisions away from delivery and infrastructure.

Overview

Publishermaksimzayats
Repositoryspecx
Skill namespecx-add-core-service
Stars
201
Forks
34
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by maksimzayats on GitHub. Read the source before you install it.

Installation

Install the Specx Add Core Service 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/maksimzayats/specx/tree/main/.agents/skills/specx-add-core-service
  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/maksimzayats/specx.git /tmp/specx
mkdir -p .claude/skills
cp -r /tmp/specx/.agents/skills/specx-add-core-service .claude/skills/specx-add-core-service
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Specx Add Core Service 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 Specx Add Core Service 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 Specx Add Core Service 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.

specx Add Core Service

Use this skill for reusable core behavior that is smaller than an application action. Read references/service.md before writing the service.

Workflow

  1. Confirm this is reusable business/application behavior, not a small replaceable ability. Use BaseCapability instead for one narrow injectable thing.
  2. Name the behavior, not a vague role, and always use the Service suffix: InvoicePricingService, AccessPolicyService, OrderAllocationService, SubscriptionRenewalService.
  3. Put it under core/<scope>/services/<behavior>.py.
  4. Choose exactly one foundation base: BasePureService, BaseReadService, or BaseEffectService.
  5. Do not add or use a generic BaseService.
  6. Inject concrete project collaborators when there is one implementation.
  7. Inject ports/ABCs only for external IO, framework-bound dependencies, or multiple real implementations. Do not create an interface only to make a concrete collaborator mockable.
  8. Add a docstring that explains the service scope and includes a concrete Example:.
  9. Keep methods keyword-only after self.
  10. Do not open UoW scopes in services. Use cases own transaction lifecycle and pass active UoWs into read/effect services when needed.
  11. Add flat unit tests that receive the native pytest container fixture, register local doubles or inline mocks before resolution, and resolve the service with container.resolve(ServiceClass).

Operational probe services may live under core/health when readiness checks any required external dependency or policy is reused across deliveries. Keep simple process liveness in delivery. Use a pure service for reusable liveness policy and a read service for readiness coordination. Readiness services depend on gateway ports, not SQLAlchemy, Redis, SDKs, or delivery frameworks directly. Technical readiness adapters must bound external checks with short timeouts so a probe cannot hang indefinitely.

Code Style

Use blank lines as logical separators in all code. Keep related statements together, but separate independent setup, action, assertion, response, branch, and transformation groups so long blocks stay readable.

References

  • references/service.md - class shape, dependency choices, UoW parameter rules, and unit-test examples.

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 Specx Add Core Service AI skill do?

Add or refactor a specx core scope service. Use when implementing focused reusable business/application behavior under a core scope services package, extracting logic from a use case, injecting deterministic collaborators, accepting an active unit of work, choosing between Service and Capability, or keeping business decisions away from delivery and infrastructure.

Why use Specx Add Core Service on TypingMind?

Because you install it once and use it with any model. Specx Add Core Service 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 Specx Add Core Service in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/maksimzayats/specx/tree/main/.agents/skills/specx-add-core-service. 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 Specx Add Core Service?

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 Specx Add Core Service?

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

Is the Specx Add Core Service AI skill free?

Yes. It is published on GitHub by maksimzayats 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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