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competlab

competlab-mcp-server

get_project

Retrieve project details and dimension monitoring freshness for competitive intelligence. Check last updated timestamps for pricing, content, positioning, tech stacks, and AI visibility before fetching specific 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)
Behavior4/5

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

No annotations provided, so description carries full safety burden. Successfully discloses 'Read-only' nature and return format 'Returns JSON object'. Describes scope of returned data (freshness timestamps vs full data). Missing error behavior for invalid project IDs (though schema regex pattern partially covers this).

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?

Three sentences with zero waste. Front-loaded with capabilities (what details are retrieved), followed by usage workflow, ending with safety/return contract. Every clause earns its place.

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?

No output schema and no annotations, yet description adequately explains return contents (specific dimensions covered, freshness data, prompts, status) and positions tool correctly within 20+ tool ecosystem. Could enhance with error case description, but sufficient for single-parameter metadata retrieval 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% with projectId pattern and description 'Project ID (from list_projects)'. Description references list_projects in usage guidance, implicitly reinforcing the parameter source, but doesn't add syntax, format, or semantic details beyond the schema. Baseline 3 appropriate for high coverage.

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?

Clear specific verb 'Get' + resource 'project details'. Uniquely identifies what's returned (per-dimension monitoring freshness across 5 specific dimensions, AI monitoring prompts, status) distinguishing it from sibling detail tools that fetch actual dimension data rather than metadata/freshness.

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

Usage Guidelines5/5

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

Explicit workflow guidance: 'Use this after list_projects' establishes prerequisite sequence. Clear purpose clause 'to check when each dimension was last updated before fetching dimension data' distinguishes it from 15+ sibling data-fetching tools (get_content_dashboard, get_pricing_history, etc.).

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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