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List Brain Documents

aidelly_list_brain_documents
Read-onlyIdempotent

List the workspace's Brain documents (brand guidelines, reports, style guides and similar files), newest first, with title, type, size and text-extraction status. Filter by document_type or status. Text is not included: use aidelly_get_brain_document to read it. The Brain also indexes each document for aidelly_search_brain. Read-only.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional query overrides for endpoints with sparse parameter schemas.
statusNoText extraction status.
brand_idNo
workspace_idNoWorkspace to operate in: the `id` of a workspace returned by aidelly_list_workspaces. Optional for read operations; required when creating content.
document_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint, so the description's closing 'Read-only' is redundant. However, it adds real behavioral context the annotations don't carry: newest-first sort order, the exact fields returned, the absence of text bodies, and the fact that each document is indexed for aidelly_search_brain.

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 tight sentences that front-load the core action, then filtering, then the routing caveat. Slight waste in restating 'Read-only' which the annotations already provide.

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?

With no output schema, the description usefully enumerates the returned fields and explains the text-extraction status concept, which is enough to call the tool correctly. It does not mention result limits or pagination behavior, which is the main remaining gap for a list endpoint.

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 60%, so the schema documents some parameters; the description covers document_type and status filtering but says nothing about workspace_id, brand_id, or the sparse 'query' override object. It adds the ordering semantic but does not compensate for the undocumented parameters, so baseline 3 is right.

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) and resource (workspace's Brain documents), enumerates the document kinds it covers, and specifies the ordering and returned fields. It also names the sibling tools (aidelly_get_brain_document, aidelly_search_brain) so an agent can distinguish it from them without opening a 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?

Explicitly says to filter by document_type or status, and states plainly that text is not included and that aidelly_get_brain_document must be used instead to read content. This routes the agent away from a foreseeable mistake (listing to get document 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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