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Dynamic Tools

Organization
opencrabs
dynamic-tools

Runtime tool management with tool_manage and tools.toml format. Create, enable, disable, reload tools without restart. (/dynamic-tools, tool_manage, runtime tools)

Overview

Publisheropencrabs
Repositoryopencrabs
Skill namedynamic-tools
Stars
981
Forks
105
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Dynamic Tools 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/opencrabs/opencrabs/tree/main/src/docs/reference/templates/skills/dynamic-tools
  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/opencrabs/opencrabs.git /tmp/opencrabs
mkdir -p .claude/skills
cp -r /tmp/opencrabs/src/docs/reference/templates/skills/dynamic-tools .claude/skills/dynamic-tools
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dynamic Tools 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 Dynamic Tools 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 Dynamic Tools 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.

Dynamic Tools Reference

Runtime tool creation — define tools in ~/.opencrabs/tools.toml and they become callable immediately without restart or rebuild.

tool_manage Meta-Tool

ActionRequiredWhat
list—Show all dynamic tools with enabled/disabled status
addname, description, executor, method/commandCreate new tool (persists to tools.toml)
removenameDelete a tool
enable / disablenameToggle without removing
reload—Hot-reload from tools.toml

Executor Types

Two executor types, set via the executor field:

ExecutorField
executor = "shell"command — shell command string
executor = "http"method, url — HTTP method and endpoint

Parameter Handling

Every tool parameter defined in [[tools.params]] becomes available in two ways:

  1. $OPENCRABS_PARAMS — Environment variable pointing to a temporary JSON file containing all params with their current values. The file is created before the command runs and cleaned up after. Use with --params-file flags or read directly inside scripts:

    toml
    command = "/usr/local/bin/mycli send --params-file \"$OPENCRABS_PARAMS\""

    Inside a shell script, read the file directly:

    sh
    #!/bin/sh
    # $OPENCRABS_PARAMS points to a JSON file with all tool params
    action=$(jq -r '.action // "default"' "$OPENCRABS_PARAMS")
    payload=$(jq -r '.payload // empty' "$OPENCRABS_PARAMS")
    exec mycli "$action" --data "$payload"
  2. {{param_name}} — Inline template substitution. Replaced with the string value of the parameter:

    toml
    command = "curl -s -H \"Authorization: Bearer {{api_key}}\" {{endpoint}}"

Conditional Sections

Wrap template content with {{#param_name}}...{{/param_name}} to include only when the parameter is non-null and non-empty:

toml
command = """curl -s {{#query}}-G --data-urlencode "q={{query}}"{{/query}} {{url}}"""

Coercion Rules

Each param can specify how null/empty values are handled before being written to $OPENCRABS_PARAMS:

coerce_empty_to / coerce_null_toEffect
"keep" (default)Pass null/empty as-is into the JSON
"omit"Drop the key entirely from $OPENCRABS_PARAMS JSON
"null"Convert to JSON null
"error"Reject the tool call with a validation error

Example:

toml
[[tools.params]]
name = "query"
type = "string"
required = false
default = "null"
coerce_empty_to = "null"

tools.toml Format

Shell Executor

toml
[[tools]]
name = "send_notification"
description = "Send a notification via the notification service"
executor = "shell"
enabled = true
requires_approval = true
timeout_secs = 30
command = "/usr/local/bin/notify-send --params-file \"$OPENCRABS_PARAMS\""

[[tools.params]]
name = "channel"
type = "string"
description = "Notification channel: email, slack, or push"
required = true

[[tools.params]]
name = "message"
type = "string"
description = "Message body"
required = true

[[tools.params]]
name = "priority"
type = "string"
description = "Priority level: low, normal, high"
required = false
default = "normal"

HTTP Executor

toml
[[tools]]
name = "check_api_health"
description = "Check if the production API is responding"
executor = "http"
enabled = true
method = "GET"
url = "https://api.example.com/health"

[tools.headers]
Authorization = "Bearer {{api_key}}"

Rate Limiting

toml
[tools.rate_limit]
requests = "10"
window = "1m"

Full Example — CLI tool with $OPENCRABS_PARAMS

toml
[[tools]]
name = "search_index"
description = "Search indexed documents by query"
executor = "shell"
enabled = true
requires_approval = false
timeout_secs = 60
command = "/usr/local/bin/doc-search --params-file \"$OPENCRABS_PARAMS\" 2>&1"

[[tools.params]]
name = "query"
type = "string"
description = "Search text"
required = true

[[tools.params]]
name = "limit"
type = "integer"
description = "Max results to return"
required = false
default = "50"

[[tools.params]]
name = "source"
type = "string"
description = "Document source filter"
required = false
default = ""

How It Works

  1. On startup, tools from tools.toml load into the ToolRegistry alongside compiled tools.
  2. Dynamic tools appear in the LLM's tool list — the agent calls them autonomously.
  3. Use tool_manage add to create new tools at runtime.
  4. Use tool_manage reload to pick up manual edits to tools.toml.
  5. Unlike commands.toml (user-triggered slash commands), these are agent-callable tools.
  6. Shell commands run via sh -c — $OPENCRABS_PARAMS is set as an environment variable pointing to the real temp JSON file path. The file is cleaned up after command completion.

Frequently asked questions

What does the Dynamic Tools AI skill do?

Runtime tool management with tool_manage and tools.toml format. Create, enable, disable, reload tools without restart. (/dynamic-tools, tool_manage, runtime tools)

Why use Dynamic Tools on TypingMind?

Because you install it once and use it with any model. Dynamic Tools 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 Dynamic Tools in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/opencrabs/opencrabs/tree/main/src/docs/reference/templates/skills/dynamic-tools. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dynamic Tools?

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 Dynamic Tools?

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

Is the Dynamic Tools AI skill free?

Yes. It is published on GitHub by opencrabs 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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