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doc_assistant

Simplify video application development by organizing and managing document-related tasks efficiently within VideoDB Director.

Instructions

Context for creating video applications using VideoDB

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'doc_assistant' tool, registered via @mcp.tool decorator. It fetches VideoDB documentation from DOCS_ASSISTANT_TXT_URL and returns it as a string.
    @mcp.tool(
        name="doc_assistant",
        description="Context for creating video applications using VideoDB",
    )
    def doc_assistant() -> str:
        try:
            response = requests.get(DOCS_ASSISTANT_TXT_URL)
            response.raise_for_status()
            return response.text
        except requests.exceptions.RequestException as e:
            return f"Error: Unable to fetch data from URL. Details: {str(e)}"
  • Similar handler function registered as a resource via @mcp.resource with URI 'videodb://doc_assistant'. Implements the same logic as the tool version.
    @mcp.resource(
        "videodb://doc_assistant",
        name="doc_assistant",
        description="Context for creating video applications using VideoDB",
    )
    def doc_assistant() -> str:
        try:
            response = requests.get(DOCS_ASSISTANT_TXT_URL)
            response.raise_for_status()
            return response.text
        except requests.exceptions.RequestException as e:
            return f"Error: Unable to fetch data from URL. Details: {str(e)}"
  • Package __init__.py that imports and exports 'doc_assistant' function, making it available for import from the package.
    from videodb_director_mcp.main import (
        call_director,
        play_video,
        code_assistant,
        doc_assistant,
    )
    
    
    __all__ = ["call_director", "play_video", "code_assistant", "doc_assistant"]
  • Defines DOCS_ASSISTANT_TXT_URL constant used by the doc_assistant handler to fetch the documentation content.
    CODE_ASSISTANT_TXT_URL = "https://videodb.io/llms-full.txt"
    
    DOCS_ASSISTANT_TXT_URL = "https://video-db.github.io/agent-toolkit/context/docs/docs_context.md"
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description hints at providing 'context' for video application creation, but it doesn't specify what this entails—whether it's informational, instructional, or involves data retrieval. It lacks details on permissions, side effects, or response format, leaving significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence: 'Context for creating video applications using VideoDB.' It's front-loaded and wastes no words, making it efficient. However, it could be more structured if it included clearer purpose or usage hints, but as-is, it's appropriately sized for its limited content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description doesn't need to explain parameters or return values. However, the description is vague about the tool's purpose and behavior, and with no annotations, it leaves gaps in understanding what 'context' means and how it aids in video application creation. It's minimally adequate but lacks depth for a tool that might involve complex operations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the schema description coverage is 100%, so there's no need for parameter details in the description. The description doesn't mention parameters, which is appropriate. A baseline of 4 is given for zero-parameter tools, as there's no semantic gap to fill beyond what the schema already indicates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Context for creating video applications using VideoDB' is vague about what the tool actually does. It mentions 'context' and 'creating video applications' but doesn't specify a clear action or resource. It's not a tautology since it adds some information beyond the name 'doc_assistant', but it fails to distinguish what specific function this tool performs compared to its siblings like 'code_assistant' or 'play_video'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'creating video applications' but doesn't clarify if this is for setup, documentation, or another purpose, nor does it reference sibling tools like 'code_assistant' or 'play_video' for comparison. There's no explicit or implied context for usage decisions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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