Skip to main content
Glama

Data Parrot AI Revenue Analyst for HubSpot

Explore Available Data Parrot Data

describe_data_catalog
Read-onlyIdempotent

Discover supported fields, AI assessment meanings, filters, allowed values, and workspace-defined properties when these are unknown. Call with no arguments for the compact manifest, then request an advertised section and detail. A search requires both section and detail. This tool describes available data and how to query it; it does not return business evidence.

Input Schema

NameRequiredDescriptionDefault
pageNo
detailNo
searchNoCase-insensitive search over catalog values, requiring both section and detail. For deal fields, use section='deals', detail='fields', search='forecast'.
sectionNo
field_idNo
lifecycleNo
page_sizeNo
option_pageNo
option_page_sizeNo

Output Schema

NameRequiredDescriptionDefault
dataYes
kindYes
toolYes
summaryYes
limitationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / search / description
      Added value: +"Case-insensitive search over catalog values, requiring both section and detail. For deal fields, use section='deals', detail='fields', search='forecast'."
  2. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so safety needs no restating. The description adds real behavioral context beyond that: the progressive-disclosure pattern (empty call yields a manifest that advertises valid sections/details) and the requirement that search be paired with section+detail. It doesn't cover pagination or option-paging behavior, which the other params imply.

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?

Three dense sentences, front-loaded with purpose, then workflow, then scope boundary; nothing is padding. The opening clause ('Discover ... when these are unknown') is slightly tangled but costs little.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is rightly omitted, and the manifest-then-section workflow is well conveyed. However, with 9 parameters at 11% schema coverage, the description leaves most callable knobs (lifecycle, field_id, the two paging pairs) unexplained, which is the main missing piece for correct invocation.

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

Parameters2/5

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

Schema description coverage is only 11% and only the 'search' param is documented there, so the description is the main hope for the remaining eight. It clarifies section/detail as manifest-advertised keys, but leaves lifecycle, field_id, page, page_size, option_page, and option_page_size completely opaque in both schema and description — a significant gap for a 9-param tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Discover') and resource (supported fields, AI assessment meanings, filters, allowed values, workspace-defined properties) and adds an explicit negative scope: 'it does not return business evidence,' which separates it from the get_* siblings. It is slightly list-like rather than a single crisp statement, but an agent can tell it is a metadata/catalog inspector, not a data fetcher.

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?

It gives a concrete trigger ('when these are unknown') and a step-by-step call sequence: no arguments for the compact manifest, then request an advertised section and detail, with the constraint that search requires both section and detail. It does not name any sibling alternative (e.g. calling get_deals directly instead of exploring), so the when-not guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources