Tiger Skills

io.github.timescalePublished by GitHub account timescalev0.1.4Updated Oct 24, 2026

Provider agnostic skills implementation, with skills sourced from local paths or GitHub repositories

VerifiedSTDIODesktop onlyKnowledge & MemoryDeveloper Tools

Overview

AI-generated overview

Loads modular skill packages from local directories or GitHub repositories and exposes them to any MCP-compatible agent.

What you can do
Tiger Skills implements a provider-agnostic skills system compatible with Anthropic's skill format. It reads a YAML configuration listing local skill directories or GitHub repositories, each skill being a folder with a SKILL.md file plus optional scripts, references and assets. Skills are exposed to the agent through progressive disclosure, and an optional subagent tool can split complex tasks into smaller agent instances. Clients can enable or disable individual skills through connection string parameters.
When to use it
Useful when you want the same curated procedural knowledge and workflows available across different LLM agents, or when you maintain skills in GitHub repositories and local folders and want them loaded on demand. It fits teams that already follow the Anthropic skill layout and want a portable way to serve it.
Requirements
Runs locally as a stdio process, installed from the npm package or the OCI image. Needs a skills.yaml configuration file (path set by SKILLS_FILE, default ./skills.yaml). A GITHUB_TOKEN is required to read private GitHub repositories. Optional settings include SKILLS_TTL, SUBAGENT_DISABLED and MCP_PATH.
Before you install
The GITHUB_TOKEN secret grants access to the GitHub repositories it is scoped for, so scope it narrowly. Skills can bundle executable scripts that the agent may run, and the subagent tool can recursively spawn further agents with additional MCP tooling configured in mcp.yaml; review skill contents before enabling them.

Installation

In SourceWeft

  1. Open Tiger Skills in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

Tiger Skills MCP Server

Emulate Claude Skills with any LLM via a Model Context Protocol (MCP) server.

What are Skills?

Skills are modular components that enhance the capabilities of an MCP-compatible agent by providing specific functionalities, workflows, and domain expertise. They transform a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

The goal is to be fully compatible with Anthropic's skill format. See their Agent Skills Spec and related documentation for more details.

An overview of the Skills spec

Skill Structure

Skills are modular, self-contained packages that extend agent capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform the agent from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.

What Skills Provide

  1. Specialized workflows - Multi-step procedures for specific domains
  2. Tool integrations - Instructions for working with specific file formats or APIs
  3. Domain expertise - Company-specific knowledge, schemas, business logic
  4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

Anatomy of a Skill

Every skill consists of a required SKILL.md file and optional bundled resources:

text
skill-name/├── SKILL.md (required)│   ├── YAML frontmatter metadata (required)│   │   ├── name: (required)│   │   └── description: (required)│   └── Markdown instructions (required)└── Bundled Resources (optional)    ├── scripts/          - Executable code (Python/Bash/etc.)    ├── references/       - Documentation intended to be loaded into context as needed    └── assets/           - Files used in output (templates, icons, fonts, etc.)
SKILL.md (required)

Metadata Quality: The name and description in YAML frontmatter determine when the agent will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").

Bundled Resources (optional)
Scripts (scripts/)

Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.

  • When to include: When the same code is being rewritten repeatedly or deterministic reliability is needed
  • Example: scripts/rotate_pdf.py for PDF rotation tasks
  • Benefits: Token efficient, deterministic, may be executed without loading into context
  • Note: Scripts may still need to be read by the agent for patching or environment-specific adjustments
References (references/)

Documentation and reference material intended to be loaded as needed into context to inform the agent's process and thinking.

  • When to include: For documentation that the agent should reference while working
  • Examples: references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specifications
  • Use cases: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
  • Benefits: Keeps SKILL.md lean, loaded only when the agent determines it's needed
  • Best practice: If files are large (>10k words), include grep search patterns in SKILL.md
  • Avoid duplication: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
Assets (assets/)

Files not intended to be loaded into context, but rather used within the output the agent produces.

  • When to include: When the skill needs files that will be used in the final output
  • Examples: assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typography
  • Use cases: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
  • Benefits: Separates output resources from documentation, enables the agent to use files without loading them into context

Progressive Disclosure Design Principle

Skills use a three-level loading system to manage context efficiently:

  1. Metadata (name + description) - Always in context (~100 words)
  2. SKILL.md body - When skill triggers (<5k words)
  3. Bundled resources - As needed by the agent (Unlimited*)

*Unlimited because scripts can be executed without reading into context window.

Configuration

Environment Variables

  • SKILLS_FILE: Path to the YAML file configuring the set of skills. Default: ./skills.yaml
  • SKILLS_TTL: Time (in milliseconds) to cache loaded skills. Default: 5 minutes

Skills Configuration File

The set of skills is configured via a YAML file. Both local directories and GitHub repositories are supported. Config can point to individual skills or collections of skills.

yaml
local-directory-collection:  # A collection of local skills stored in the `./skills` directory.  # Each skill should be in its own subdirectory with a `SKILL.md` file.  type: local_collection  path: ./skillslocal-individual-skill:  # An individual local skill stored in the `./skills/skill-name` directory.  type: local  path: ./path-to/individual/skill-nameanthropic-github-collection:  # A GitHub repo containing a collection of skills.  # Each skill should be in its own subdirectory with a `SKILL.md` file.  type: github_collection  repo: anthropics/skills  # path: ./ # not needed for this example since skills are at the root of the repo  # Optionally specify skills/paths to ignore in this collection  ignored_paths:    - .claude-plugin    - document-skills  disabled_skills:    - canvas-design  # Setting enabled_skills will _only_ load the specified skills from the collection  # enabled_skills:  #   - frontend-design  #   - webapp-testingsingle-github-skill-example:  # A GitHub repo containing an individual skill.  type: github  repo: anthropics/claude-cookbooks  path: ./skills/custom_skills/creating-financial-models

Skill names must be unique across all configured skills. Any duplicates will be ignored with a warning.

Connection string parameters

Individual clients can control the set of skills that are enabled, as well as the protocol(s) used, via parameters in the connection string.

  • enabled_skills: Comma-separated list of skill keys to enable. If not provided, all configured skills are enabled.
  • disabled_skills: Comma-separated list of skill keys to disable. If not provided, no skills are disabled.
  • tools=0: Disable all tools (for resource-only integration).
  • resources=0: Disable all resources (for tool-only integration).
Example
text
http://tiger-skills-mcp-server/mcp?disabled_skills=foo,bar&resources=0

Subagent Task Execution

This MCP server (optionally) provides a subagent tool that can be used to break up complex tasks into smaller subtasks, each handled by its own agent instance. This is useful for tasks that require multiple steps, especially when those steps may require consuming large amounts of data in LLM context.

The subagent will automatically have access to the same set of skills as configured for the view skill tool, as well as the ability to (recursively) invoke further subagents. In addition, a mcp.yaml configuration file can be provided to specify additional tooling to be made available to the subagent.

If you do not wish to use subagents, you can set SUBAGENT_DISABLED=true in the environment to disable the tool.

MCP Configuration for Subagents

Create a mcp.yaml file to specify additional tools for the subagent to have accessible. This file is read from the root directory by default, or you can specify a different path via the MCP_PATH environment variable.

Only the streamable HTTP transport is supported at this time.

yaml
pg_aiguide:  type: http  url: https://mcp.tigerdata.com/docs

Development

Cloning and running the server locally.

bash
git clone [email protected]:timescale/tiger-skills-mcp-server.git

Building

Run ./bun i to install dependencies and build the project. Use ./bun watch to rebuild on changes.

You will need a GitHub token with the correct scopes. Here is a direct link to create such a new token.

Create a .env file based on the .env.sample file.

bash
cp .env.sample .env

Then update the GITHUB_TOKEN value in .env.

Testing

The MCP Inspector is a very handy to exercise the MCP server from a web-based UI.

bash
./bun inspector
Test via HTTP
bash
./bun watch http
FieldValue
Transport TypeStreamable HTTP
URLhttp://localhost:3001/mcp
Test via stdio
bash
./bun watch stdio
FieldValue
Transport TypeSTDIO
Commandnode
Argumentsdist/index.js
Testing in Claude Desktop

Create/edit the file ~/Library/Application Support/Claude/claude_desktop_config.json to add an entry like the following, making sure to use the absolute path to your local tiger-skills-mcp-server project, and use a valid GitHub token.

json
{  "mcpServers": {    "tiger-skills": {      "command": "node",      "args": [        "/absolute/path/to/tiger-skills-mcp-server/dist/index.js",        "stdio"      ],      "env": {        "GITHUB_TOKEN": "ghp_whatever"      }    }  }}

Source: README.md at commit f767fb4

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.4LatestSep 16, 2026

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  • Tools listed15 pts

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