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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.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds valuable behavioral context: data source (CF analytics-engine), no PII, caching duration (5min-1h). No contradictions.

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 concise paragraphs: purpose, use cases (bulleted), source/caching info. Front-loaded with key action. Every sentence adds value. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Returns described as top tools, top packs, total call volume but no detail on format, limits, or pagination. Since no output schema, description should clarify structure. Simple tool, so score is adequate but not fully complete.

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?

Single parameter 'window' with 100% schema coverage. Description adds practical guidance on how window choice affects results (hot vs. steady-state), going beyond schema enum. Could further clarify default behavior.

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?

Description clearly states 'Returns the top tools, top packs, and total call volume over a recent window' with specific verb and resource. Distinguishes from sibling tools like discover_tools and search_within by focusing on aggregated trending data rather than search or discovery.

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 lists three use cases and explains window selection (shorter for hot, longer for steady-state). Does not explicitly state when not to use, but context is clear. Could mention alternatives like discover_tools for non-trending discovery.

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

A3.7/5.0
Disambiguation2/5

Although many tools are individually well-described, there are several overlapping clusters: three ask_pipeworx variants, multiple polymarket edge/arbitrage tools, and AI-visibility checks vs their competitor-comparison wrapper. An agent can easily pick the wrong one because the boundaries (beta vs stable, grounded vs routed, edge vs arbitrage) are subtle despite the verbose descriptions.

Naming Consistency3/5

The set is consistently snake_case and mostly readable, so naming is not chaotic. However, the pattern is mixed: some tools use entur_/polymarket_/pipeworx_ prefixes, others are bare verbs (remember, recall, forget), and some are noun phrases (entity_profile, pipeworx_trending). The ask_pipeworx family also doesn't follow the pipeworx_ prefix convention used by neighboring tools.

Tool Count2/5

34 tools is well past the healthy range for a focused MCP server, and only three tools relate to the Entur transport domain implied by the server name. The other 31 tools form a separate, broad data/prediction-market product that appears bolted on, making the count inappropriate for the apparent purpose.

Completeness2/5

The Entur transport subset has stops search, departures, and journey planning, but misses common public-transport needs such as disruptions, service alerts, and fare/ticket information. The broader tool set is extensive but lacks a single coherent domain to be complete against, leaving the overall surface scattered and hard to trust as an integrated whole.