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vish288

mcp-coda

by vish288
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Coda List Pack Formula Analytics

coda_list_pack_formula_analytics
Read-onlyIdempotent

List per-formula analytics for a Coda pack to monitor invocation counts, error rates, and execution times. For pack makers only.

Instructions

List analytics data for individual formulas within a pack.

Returns per-formula invocation counts, error rates, and execution times. Only available to the pack maker.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of results (1-200)
cursorNoPagination cursor from a previous response
pack_idYesThe pack ID to get formula analytics for
since_dateNoStart date for analytics (ISO 8601)
until_dateNoEnd date for analytics (ISO 8601)

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

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safe-read behavior is covered. The description adds valuable context: the return content (invocation counts, error rates, execution times) and the pack-maker-only authorization requirement, which is behavioral context beyond what annotations convey.

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?

Three short sentences with zero waste, front-loading the core action and then the return payload and a critical constraint. Every sentence earns its place.

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 a read-only list tool with full schema documentation and no output schema, the description covers purpose, return fields, and access limitation. It would be fully complete if it clarified pagination behavior or edge cases, but it is sufficient for correct invocation.

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%, so all parameters (limit, cursor, pack_id, since_date, until_date) are documented in the schema itself. The description adds no parameter formatting or usage details beyond what the schema provides, so 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 ('List analytics data') and a precise resource ('individual formulas within a pack'), clearly distinguishing it from siblings like coda_list_pack_analytics (pack-level) and coda_list_formula (formula metadata, not analytics).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides the crucial access precondition ('Only available to the pack maker'), which helps an agent decide if the call will succeed. However, it does not explicitly name alternative tools or state when to prefer pack-level vs. formula-level analytics.

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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