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vish288

mcp-coda

by vish288
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Coda Get Doc Analytics Summary

coda_get_doc_analytics_summary
Read-onlyIdempotent

Retrieve aggregated analytics across all accessible Coda docs, including total views, unique viewers, and copies. Use date and published filters for a high-level, summarized overview.

Instructions

Get aggregated analytics summary across all docs.

Returns total views, unique viewers, copies, and other metrics summed across all accessible docs. Use this for a high-level overview — use coda_list_doc_analytics for per-doc breakdown.

Input Schema

NameRequiredDescriptionDefault
since_dateNoStart date for analytics (ISO 8601)
until_dateNoEnd date for analytics (ISO 8601)
is_publishedNoFilter to published (True) or unpublished (False) docs

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.1
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "type": "object",
-  "x-fastmcp-wrap-result": true
-}New value: +null
  2. First observedv0.4.14

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety and repeatability are covered. The description still adds value by disclosing that results are summed rather than listed and that scope is limited to 'all accessible docs', which explains why counts may differ from a naive total. It does not mention rate limits or caching, keeping it short of a 5.

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?

Two sentences: the first front-loads what is returned, the second routes to the alternative. No redundancy, no filler, and the aggregation semantics precede the disambiguation.

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 read-only aggregation tool with no output schema, the description usefully previews the returned metrics and clarifies scope and the sibling relationship. It is largely complete; only minor details such as default date-range behavior or response shape are left entirely to the schema.

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 description coverage is 100% and all three filters (since_date, until_date, is_published) are documented with format and semantics in the schema itself. The description adds no further parameter meaning, so the baseline 3 applies.

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?

States a specific verb and resource ('Get aggregated analytics summary') with an explicit scope, 'across all docs', that separates it from the per-doc scoped siblings. It also enumerates the metric categories returned (views, unique viewers, copies), so an agent knows what the tool produces without opening the schema.

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?

Names an alternative tool, coda_list_doc_analytics, and the exact condition that selects it ('per-doc breakdown' vs 'high-level overview'). The when-to-use decision is fully resolved in the text.

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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