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Glama

Nws

by io.github.pipeworx-io

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. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover safety. Description adds caching behavior (5min-1h), data source (CF analytics-engine), and no PII. Provides useful behavioral 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?

Three sentences plus bulleted use cases. Every sentence adds value; no redundancy. Front-loaded with core purpose.

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?

Low complexity (1 optional param, no output schema). Description covers purpose, use cases, data source, caching, and parameter semantics fully. No gaps.

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 covers 100% with enum and description. Description adds further meaning by contrasting windows (hot vs steady-state). Adds value beyond schema.

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 window. Three specific use cases differentiate 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?

Explicitly describes when to use: for discovering hot data, confirming canonical tools, and alignment checking. Implicitly excludes query-based tools via context, but no explicit when-not-to-use.

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

All Nws toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., multiple Polymarket analysis tools, several query tools (ask_pipeworx, deep_research, compare_entities, entity_profile) with unclear boundaries. Agents may struggle to choose the correct tool.

Naming Consistency3/5

While most names use snake_case, there is no consistent prefix pattern across subdomains (e.g., 'ask_', 'get_', 'polymarket_', 'pipeworx_'). Some names like 'bet_research' and 'deep_research' follow different conventions within the same domain.

Tool Count2/5

34 tools is excessive for a server named 'Nws' that primarily suggests weather. The set covers many unrelated domains (prediction markets, npm scanning, memory), making the scope unfocused and overloaded.

Completeness3/5

The server has decent coverage for prediction markets and company financials, but weather tools are limited to basic forecasts/alerts, lacking radar, climate, or historical data. Other domains like npm scanning seem tacked on.

Resources