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competlab

competlab-mcp-server

list_schedules

Retrieve monitoring schedules for all five competitive dimensions to check next run times, verify intervals, and confirm enabled status.

Instructions

Get monitoring schedules for all 5 dimensions. Returns enabled/disabled status, interval in days, next run timestamp, and last run timestamp per dimension. Dimension names use marketing names (tech-trust, content, positioning, pricing, ai-visibility). Use this to check when the next monitoring run is due or verify scheduling configuration. Read-only. Returns JSON array.

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 burden. Explicitly declares 'Read-only' safety trait, discloses return format ('Returns JSON array'), and details response contents (enabled/disabled status, intervals, timestamps). Also warns that dimension names use marketing names (tech-trust, etc.), which prevents confusion. Missing rate limits or error behaviors, but strong for a list operation.

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?

Extremely efficient: front-loaded purpose, followed by return value specification, domain context (marketing names), and usage guidance. Every sentence delivers distinct value. No redundant or filler text despite covering multiple aspects (scope, return values, usage, safety).

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 exists, but description compensates effectively by enumerating returned fields (status, intervals, timestamps) and format (JSON array). For a single-parameter list tool, coverage is sufficient, though pagination behavior could be mentioned.

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?

Input schema has 100% description coverage ('Project ID (from list_projects)'). Description adds no parameter-specific context, but with complete schema documentation, no additional text is necessary. Baseline 3 is appropriate when schema does the heavy lifting.

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?

Description opens with specific verb 'Get' + resource 'monitoring schedules' + scope 'all 5 dimensions'. Clearly distinguishes from sibling dashboard/history tools (get_*_dashboard, get_*_history) by focusing on scheduling configuration rather than monitoring results.

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 states 'Use this to check when the next monitoring run is due or verify scheduling configuration', providing clear context for when to invoke. Lacks explicit 'when not to use' or named alternatives (e.g., distinguishing from get_*_run_detail), but establishes the specific use case well.

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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