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create_collection

Create a new collection to organize threat models, security components, and mitigations within the Devici security platform.

Instructions

Create a new collection

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
other_propertiesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main MCP tool handler for 'create_collection'. It takes name, optional description and other properties, constructs the data dict, calls the API client, and returns the result as string.
    @mcp.tool()
    async def create_collection(name: str, description: str = None, **other_properties) -> str:
        """Create a new collection"""
        async with create_client_from_env() as client:
            collection_data = {"name": name}
            if description:
                collection_data["description"] = description
            collection_data.update(other_properties)
            result = await client.create_collection(collection_data)
            return str(result)
  • Helper method in the DeviciAPIClient class that makes the HTTP POST request to the /collections endpoint to create a new collection.
    async def create_collection(self, collection_data: Dict[str, Any]) -> Dict[str, Any]:
        """Create new collection."""
        return await self._make_request("POST", "/collections", json_data=collection_data)
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers none. It doesn't indicate whether this is a safe operation, what permissions are required, whether it's idempotent, what happens on failure, or what the typical response looks like. For a creation tool with mutation implications, this lack of transparency is a significant gap that could lead to incorrect usage.

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

Conciseness5/5

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

The description is extremely concise at just three words, with zero wasted language. It's front-loaded with the core action and resource. While this conciseness comes at the expense of completeness, the structure itself is optimal for what little information it provides.

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

Completeness1/5

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

Given the tool's complexity (creation/mutation operation with 3 parameters), the complete lack of annotations, and the schema's 0% description coverage, the description is woefully inadequate. While an output schema exists (which might help with return values), the description doesn't address critical aspects like behavioral traits, parameter meanings, or usage context. This leaves too many gaps for effective tool selection and invocation.

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

Parameters1/5

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

The description provides no information about parameters, while the input schema has 0% description coverage (titles only, no descriptions). With 3 parameters (name, description, other_properties) and no semantic context in either the description or schema, an AI agent cannot understand what these parameters mean, what format they expect, or how they affect the collection creation. The description fails to compensate for the schema's deficiencies.

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 'Create a new collection' is a tautology that essentially restates the tool name 'create_collection'. It specifies the verb 'Create' and resource 'collection', but lacks any distinguishing details about what a collection represents in this context or how it differs from similar resources like 'threat_model' or 'team' that appear in sibling tools. The purpose is clear at a basic level but fails to provide meaningful differentiation.

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

Usage Guidelines1/5

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 doesn't mention prerequisites (e.g., permissions needed), when not to use it, or how it relates to sibling tools like 'create_threat_model' or 'get_collection'. Without any contextual cues, an AI agent would struggle to determine appropriate usage scenarios.

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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