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Glama

Ask what X is saying

x_pulse
Destructive

Search live X conversations on a topic and get cited answers about what practitioners are saying now, with engagement evidence and a configurable budget cap.

Instructions

An agent searches X live and answers what practitioners are saying about a topic right now, with per-claim citations and engagement evidence. Slow (about 60 seconds) and the dearest search: ask one sharp question. SPENDS CREDIT: about $0.25 of engine cost a default call, billed with the plan's margin; budgetUsd caps it (default 2, max 10) and chargedUsd says what it cost. Needs the write scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe topic or question to sense the live X conversation on.
budgetUsdNoOptional: the most this call may spend, in dollars, default 2, max 10.

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

A4.6/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: ~60s latency, ~$0.25 engine cost, billing with plan margin, budgetUsd capping behavior, chargedUsd as the cost report, and the required write scope. These are exactly the operational facts an agent needs before committing to an expensive call and align with readOnlyHint=false.

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?

Front-loaded with purpose before cost and latency caveats; every sentence carries operational weight. Slightly dense with billing detail, but nothing is wasted.

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?

For a credit-spending, open-world search with an output schema already covering returns, the description supplies the missing pieces — latency, cost, budget cap, auth scope. An agent has everything needed to decide and invoke correctly.

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 already 100%, but the description reinforces budget semantics ('budgetUsd caps it, default 2, max 10') and introduces chargedUsd as the returned cost value, which the input schema does not cover. Marginal but genuine added meaning over the structured fields.

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 and resource: 'An agent searches X live and answers what practitioners are saying about a topic right now.' It names the differentiators (per-claim citations, engagement evidence) that distinguish it from siblings like current_pulse, news_search, or web_search.

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?

Gives clear context for use: 'Slow (about 60 seconds) and the dearest search: ask one sharp question,' which implicitly steers agents toward economical, targeted queries. It stops short of naming a cheaper alternative sibling (e.g. current_pulse, web_search), so the when-not-to-use routing is inferred rather than explicit.

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