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competlab

competlab-mcp-server

get_project

Retrieve project details with per-dimension monitoring freshness for tech, content, positioning, pricing, and AI visibility. Check last update times before fetching dimension data.

Instructions

Get project details including per-dimension monitoring freshness (techTrust, content, positioning, pricing, aiVisibility), AI monitoring prompts, and overall status. Use this after list_projects to check when each dimension was last updated before fetching dimension data. Read-only. Returns JSON object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)
Behavior2/5

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

No annotations are provided, so the description bears full responsibility. It only notes 'Read-only' and 'Returns JSON object.' Lacks details on authentication, rate limits, or idempotency. Minimal behavioral disclosure.

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?

Two concise sentences with front-loaded key details. No wasted words. Highly efficient.

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

Completeness4/5

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

Given no output schema, the description adequately mentions return object contents. Could be more thorough about the exact structure, but sufficient for a simple get tool.

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

Parameters3/5

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

Schema coverage is 100% (projectId with description). The tool description adds no new parameter information beyond what is already in the schema. Baseline of 3 applies.

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

Purpose5/5

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

The description clearly states the action ('Get project details') and specifies the contained information (per-dimension freshness, AI monitoring prompts, status). It distinguishes itself from sibling dimension-specific tools by being the main project detail endpoint.

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

Usage Guidelines4/5

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

Explicitly advises to use after list_projects and before fetching dimension data, providing clear workflow guidance. Does not explicitly mention when not to use, but the context is sufficient.

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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