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competlab

competlab-mcp-server

get_content_run_detail

Retrieve competitor content intelligence from any historical run to investigate strategy changes and compare performance between time periods.

Instructions

Get full competitor-by-competitor Content Intelligence data for a specific historical run. Returns the same data structure as get_content_dashboard but for a past point in time. Use this to investigate content strategy changes between runs. Requires runId from get_content_history. Read-only. Returns JSON object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)
runIdYesRun ID (from get_content_history)
Behavior3/5

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

No annotations provided, so description carries full safety burden. Correctly discloses 'Read-only' nature and return type ('Returns JSON object'). Adds context about data structure equivalence to get_content_dashboard. Missing: error handling, pagination, data volume, or cache 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?

Four efficient sentences covering purpose, sibling relationship, usage guidance, and prerequisites/safety. Information-dense without redundancy. Final sentence combines multiple facts (prereq, read-only, return type) but remains readable.

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?

For a detail-fetch tool without output schema, description adequately covers: what data (competitor-by-competitor Content Intelligence), temporal scope (historical run), data format (JSON), and workflow integration (requires history lookup). Could strengthen by mentioning relationship to get_content_changelog or data retention limits.

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 clear descriptions ('Project ID', 'Run ID'). Description adds provenance context for runId ('from get_content_history'), establishing the tool chain. Baseline 3 appropriate since schema already documents parameter semantics fully.

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?

Excellent specificity: verb 'Get', resource 'competitor-by-competitor Content Intelligence data', scope 'for a specific historical run'. Explicitly differentiates from get_content_dashboard by contrasting 'past point in time' vs implied current data.

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?

Provides explicit use case ('investigate content strategy changes between runs') and prerequisite chain ('Requires runId from get_content_history'). References sibling get_content_dashboard for structural comparison. Lacks explicit 'when-not-to-use' (e.g., 'don't use for current data') but implication is clear.

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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