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competlab

competlab-mcp-server

get_tech_trust_dashboard

Assess competitor websites by analyzing security headers, trust signals, technology stack, and AI insights. Identify strengths and weaknesses to guide strategy.

Instructions

Get the latest Tech & Trust Profile for all competitors. Returns security headers (grade A-F, HSTS, CSP, X-Frame-Options), trust signals (compliance, reviews, social proof, certifications — 24 signals in 4 categories), technology stack (47 tech, 43 growth, 27 engagement tools), robots.txt AI bot blocking status, DNS infrastructure, and AI analysis with insights and actions. Use this for the current snapshot; use get_tech_trust_history for past runs. Note: per-competitor securityGrade and securityScore may be null and securitySignalsAvailable: { available: false, reason: 'site_uses_behavioral_protection' } may appear when a competitor uses behavioral bot protection — treat as "unscannable" rather than failing. Read-only. Returns JSON object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)
Behavior5/5

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

With no annotations, the description fully covers behavioral traits: it explains null values for securityGrade/securityScore and the 'unscannable' case with behavioral protection, and declares read-only and JSON output.

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 moderately long but well-structured, front-loading the main purpose and then detailing returned data. Every sentence adds value, though it could be slightly more concise without losing information.

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

Completeness5/5

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

Given no output schema, the description thoroughly explains the comprehensive return data (various signals, categories) and edge cases. It provides enough context for an AI agent to use the tool correctly.

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?

The single parameter (projectId) has full schema description coverage (100%), so the description does not need to add much. It mentions 'Project ID (from list_projects)' in the schema, which is sufficient. The description does not elaborate further, but given the simple parameter, this is adequate.

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 tool returns the latest Tech & Trust Profile for all competitors, listing specific data categories (security headers, trust signals, tech stack, etc.). It distinguishes from the sibling 'get_tech_trust_history' by specifying 'current snapshot vs. past runs'.

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?

The description explicitly says 'Use this for the current snapshot; use get_tech_trust_history for past runs,' providing clear when-to-use guidance and a direct alternative. It also states 'Read-only,' indicating safe usage.

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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