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get_concept_articles

Read-only

Retrieve concept articles from your knowledge base with filters for cluster, brain, or text search. Get title, slug, word count, and backlink count.

Instructions

Query compiled concept articles from your knowledge base. Filter by cluster_id, brain_id, or free-text search against title and body. Returns title, slug, word count, and backlink count per article.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax articles to return (default 10)
queryNoOptional text search against title and body
brain_idNoFilter by Brain UUID
cluster_idNoFilter by topic_cluster UUID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
articlesYes
Behavior4/5

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

Annotations already declare readOnlyHint=true. The description adds that it returns title, slug, word count, and backlink count per article, providing useful behavioral context beyond the schema.

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, no wasted words. First sentence states purpose, second lists filters and output. Front-loaded and efficient.

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?

Covers purpose, filters, and return structure. With output schema present, it doesn't need more detail. Could mention ordering or pagination, but not essential.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds meaning by grouping filters and stating output fields (title, slug, word count, backlink count), helping the agent understand parameter effects.

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?

Clearly states the verb 'Query' and resource 'compiled concept articles'. Lists specific filters (cluster_id, brain_id, text search) and return fields, distinguishing it from sibling search tools like deep_search or search_knowledge.

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?

Implicitly indicates use for querying concept articles with filters. Does not explicitly mention when not to use or alternatives, but the focus on conceptual articles and specific filters differentiates it well.

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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