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Discover topics (semantic)

discover_topics

Find Smartipedia topics by meaning, not exact wording, and filter results by category, difficulty, quality, or views. Solves keyword search misses.

Instructions

Semantic/vector search with optional filters. Use when keyword search misses, or to browse a category by meaning rather than exact wording.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return
queryYesNatural-language description of what you're looking for
qualityNoFilter by quality/review status
categoryNoFilter by category
min_viewsNoOnly topics with at least this many views
difficultyNoFilter by difficulty level

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the semantic/vector search nature and optional filtering, which is helpful, but does not state that the operation is read-only, describe result ranking or format, or mention any side effects. For a search tool this is acceptable but not richly transparent.

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 concise sentences with no wasted words. The core mechanism ('semantic/vector search') is front-loaded, followed directly by actionable usage guidance. Every sentence earns its place.

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 search tool with a fully documented schema and clear usage guidance, the description is largely complete. It could note that the operation is read-only or clarify that results are relevance-ranked, but these are minor gaps given the low-risk nature of the task and the absence of an output schema.

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 100%, so all six parameters are already documented with descriptions. The description adds only the generic phrase 'optional filters,' which does not meaningfully enhance the schema's parameter explanations. Baseline 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?

Clearly states 'Semantic/vector search' with a specific resource (topics) and optional filters, distinguishing it from the likely keyword-based sibling search_topics. The contrast with 'keyword search' makes the tool's role immediately understandable.

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?

Provides explicit guidance on when to choose this tool: when keyword search misses or when browsing by meaning rather than exact wording. This effectively communicates the condition for using the tool versus the keyword-search alternative, even without naming the sibling explicitly.

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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