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Browse the catalog

catalog_list
Read-onlyIdempotent

List data, signals, tools, and workflows. Filter the catalog by the agent job, theme, item type, status, or geography.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoThe maximum number of results to return.
queryNo
themeNo
cursorNo
job_idNo
statusNo
item_typeNo
geo_archetypeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes
billingYes
warningsYes

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the safety profile is well covered. The description adds the filtering scope (job, theme, item type, status, geography) and the fact that it lists multiple item categories (data, signals, tools, workflows). This contextual value goes beyond what annotations provide. However, it doesn't describe pagination behavior or return format, though the output schema exists.

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, zero waste. First sentence states what's listed, second sentence states the filtering dimensions. Efficiently front-loaded with the core purpose.

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 filtered-list tool with an output schema, the description covers the essential purpose and all filter dimensions. With readOnly and idempotent annotations, plus an output schema, the description satisfies most needs. Minor gap: no explicit mention of pagination (cursor/limit) but these are schema-documented. It's reasonably complete for this tool type.

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 low at 13%, so the description should compensate. The description names the filtering dimensions (agent job, theme, item type, status, geography) which maps to job_id, theme, item_type, status, geo_archetype parameters. However, it doesn't explain semantics like exact-match requirement for filter values or the query text-matching behavior beyond what partial schema text hints at. It adds baseline value but not rich detail.

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 states it lists data, signals, tools, and workflows with clear filterable dimensions (agent job, theme, item type, status, geography). It clearly identifies the resource (catalog) and the action (list/browse). However, it doesn't explicitly contrast with sibling tools like catalog_describe or catalog_preview, though the verb 'list' implies browsing vs describing.

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?

The description mentions filtering capabilities which implies when this is useful (browsing by filters), but it doesn't explicitly state when NOT to use it versus alternatives like catalog_describe (for single-item detail) or catalog_request (for requesting items). The heavy overlap with catalog_describe and catalog_preview among siblings isn't clarified.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct resource-action combination (catalog items, datasets, macro data, market data, news, politics, account). Even within the market_ prefix, tools are clearly separated by resource type (quote, fundamentals, earnings, ratings, profile). No two tools appear to perform the same operation.

Naming Consistency4/5

The naming follows a consistent noun_verb pattern with domain prefixes: catalog_, datasets_, macro_, market_, news_, politics_. The verb style is consistent (describe, list, search, request, submit, return-type verbs like indicator and quote). Slight deviation with account_request_upgrade vs account_upgrade_status, and some verbs double as noun forms (quote, indicator, preview), but overall the convention is predictable.

Tool Count4/5

At 28 tools, the count is on the high side, but it serves a broad data platform spanning seven distinct domains (catalog, datasets, macro, market, news, politics, account). Each domain earns multiple tools to cover its surface, and the domains are broad enough to justify the volume. Slightly heavy, but reasonable given the scope.

Completeness4/5

The surface covers the full discovery-to-delivery workflow for data: list, describe, preview, request (catalog), plus direct dataset access. Market data has symbols search, quotes, price history, fundamentals, earnings, ratings, ETFs, and profile. Minor gaps include no bulk quote or multi-ticker endpoints, and there's no tool for reading an existing catalog request's status, but core workflows are well-covered.

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