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Read Brand Document

read_brand_document
Read-onlyIdempotent

Read one indexed brand document. Returns the indexed metadata (doc_type, summary, key_topics, entities, key_quotes) plus the document body as plain text in content.text — every mime (PDF, DOCX, PPTX, XLSX, markdown, CSV, plain text). No file ids, no attaching anything on a later turn: the text is in this response. When content is null the body could not be extracted — error_code says why, and you should tell the user rather than infer contents from the title. Use AFTER list_brand_documents to pick the right document. Free, read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
document_idYesDocument to read. Get from list_brand_documents.

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations (readOnlyHint, idempotentHint) by stating it is 'Free, read-only', clarifying that content is returned inline ('No file ids, no attaching anything'), and detailing the error_code behavior when content is null. This enriches the agent's understanding of how the tool behaves in edge cases.

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 compact yet information-dense. It front-loads the primary action, then details return values, file-type coverage, the null case, and usage order—all in a few sentences. Every sentence contributes new information, with no filler.

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

Completeness5/5

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

Without an output schema, the description fully accounts for the return structure (metadata fields and content.text), explains error handling (error_code, content null), and lists supported mime types. It is sufficiently comprehensive for an agent to invoke the tool correctly and interpret results.

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?

The single parameter (document_id) is fully described in the schema ('Document to read. Get from list_brand_documents.'). The description reinforces the source of the ID but adds no new semantic information beyond the schema's own description. With 100% schema coverage, a baseline score of 3 is appropriate.

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 is specific and actionable: 'Read one indexed brand document' immediately conveys the verb and resource. It enumerates exactly what is returned (metadata fields plus content.text) and explicitly contrasts with siblings by referencing list_brand_documents as the preceding step, making the distinction clear.

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?

The description explicitly states when to use the tool—'Use AFTER list_brand_documents to pick the right document'—and provides a follow-up behavior for the null-content case ('tell the user rather than infer contents from the title'). This is precise usage guidance with no ambiguity.

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
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.