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Glama

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive. Description adds: derived from CF analytics-engine, no PII, caching behavior (5min-1h). Provides useful context beyond annotations.

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?

Efficiently structured with output summary first, then use cases, then technical details. No unnecessary words; every sentence adds value.

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 simple read-only tool with one parameter, the description covers purpose, use cases, data source, and caching. No output schema needed; complete in context.

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?

Only one parameter (window) with 100% schema coverage. Description adds meaning: 'Shorter windows surface what's hot right now; longer windows show steady-state demand,' enhancing the enum values.

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 it returns 'top tools, top packs, and total call volume over a recent window'. Uses specific verbs and resource description, distinguishing it from siblings like discover_tools or ask_pipeworx.

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?

Lists three specific use cases (discovering hot data sources, confirming popular tool, alignment). Does not explicitly state when not to use, but provides clear context for when it is appropriate.

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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TDQS

A3.6/5.0
Disambiguation2/5

Multiple tools have overlapping research/lookup purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded and validate_claim both verify claims against sources, and six polymarket_* tools overlap on edge/arbitrage detection. The three realestateapi_* tools are distinct but sit awkwardly beside 31 unrelated tools.

Naming Consistency2/5

Naming conventions are mixed: snake_case prefixed tools (realestateapi_property_search), domain-prefixed tools (polymarket_edges), verb-noun tools (ask_pipeworx, compare_entities), noun phrases (entity_profile, recent_changes), and bare verbs (remember, forget, recall). There is no consistent verb_noun pattern across the set.

Tool Count2/5

34 tools is heavy, and the vast majority belong to the Pipeworx platform rather than the Realestateapi identity — only 3 of 34 tools are real-estate specific. The count is not well-scoped for the server's stated purpose.

Completeness2/5

For a real estate API the surface is severely thin: search, detail, and skip-trace only, with no market trends, tax history, rental estimates, or comparable-sales data. For the Pipeworx meta-domain the coverage is broader, but the server presents as Realestateapi, making the domain coverage a mismatch.