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Dweeb1578

Marketing Analytics MCP Server

by Dweeb1578

demo_report_month_rollup

Retrieve pre-aggregated totals for all stored demo weeks in a given month. Returns summed leads and week details without pulling data from external sources.

Instructions

Read all stored demo weeks for a month and return pre-aggregated totals.

Pure Supabase read — no datapack pull, no HubSpot, no re-classification. The monthly skill renders the returned dict to a Google Doc tab.

Args: month: Target month as YYYY-MM (e.g. "2026-05"). Returns weeks whose week_ending falls in that month, their leads, and summed totals. A month with no stored weeks returns an explicit note.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description carries full burden. It discloses the tool's behavior as a pure read with no side effects, mentions return behavior for empty months ('explicit note'), and specifies no external integrations. This provides comprehensive behavioral transparency.

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?

The description is concise, front-loaded with the main action, and uses bullet points for the parameter. Every sentence adds value without redundancy, and the structure is clear and easy to parse.

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 the tool's simplicity (one parameter, existence of output schema), the description is nearly complete. It explains input format, behavior, and return values. Minor gap: no explicit mention of error handling for invalid month format, but the parameter description is sufficiently detailed.

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

Parameters5/5

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

The Args section fully explains the 'month' parameter: format (YYYY-MM), example, and semantics (returns weeks with week_ending in that month, leads, summed totals, note if empty). Schema coverage is 0%, so the description compensates completely for the single parameter.

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 'Read all stored demo weeks for a month and return pre-aggregated totals,' which specifies the action (Read), resource (stored demo weeks), and outcome. It distinguishes itself from siblings like demo_report_datapack and demo_report_save_week by focusing on aggregation without external pulls.

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?

The description provides clear context by stating 'Pure Supabase read — no datapack pull, no HubSpot, no re-classification,' implying it is a read-only rollup. However, it lacks explicit guidance on when to use this tool versus alternatives or when not to use it.

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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