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Glama

Search by meaning

concept_search
Read-only

Search pages, LinkedIn, and X posts by meaning, not keywords. Describe a persona or idea to find real, dated posts and articles.

Instructions

Semantic search for pages and LinkedIn or X posts that mean what you describe rather than match its words: describe a persona saying or feeling something and get real, dated posts and articles. Costs a fraction of a cent (about $0.007) from credit; budgetUsd (default 2, max 10) caps it and chargedUsd says what it cost. Needs the write scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA concept or persona description, phrased as meaning, not keywords.
budgetUsdNoOptional: the most this call may spend, in dollars, default 2, max 10.
within_daysNoOnly results published within this many days.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYes
mediaYes
outputNoThe tool's own result, shaped by the tool.
chargedUsdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.4

TDQS

A3.9/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint/openWorldHint) by disclosing the cost model (~$0.007 per call), the budget cap behavior (default 2, max 10), the chargedUsd cost readout, and an auth requirement ('Needs the write scope'). These are exactly the operational facts an agent needs before spending credit on a call.

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?

Purpose is front-loaded in the opening clause, and each subsequent clause carries a distinct payload (semantic contrast, cost, budget, scope). The second sentence is dense and slightly run-on across cost/budget/auth, but nothing is wasted.

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 an output schema present, return values need not be explained, and the description still names chargedUsd as cost feedback. For a credit-consuming search tool it covers purpose, cost, budget, and auth scope adequately; only explicit sibling routing is missing.

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 the schema already documents query, budgetUsd, and within_days; baseline is 3. The description adds color on the budget default/max and the chargedUsd cost feedback, but adds no semantics for within_days and repeats budget details already in the schema.

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?

States a specific verb and resource ('Semantic search for pages and LinkedIn or X posts') and crisply distinguishes itself from keyword tools with 'mean what you describe rather than match its words.' It does not name a specific sibling (e.g., web_search) as the contrast point, so the differentiation is conceptual rather than explicit.

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?

Conveys the usage mode well — 'describe a persona saying or feeling something' implies when this tool fits — but never states when to prefer it over keyword search siblings or when not to use it. Usage is implied rather than spelled out as an explicit condition/alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.