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Tfl

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.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare safety (readOnlyHint, idempotentHint), and the description adds valuable behavioral context: data source (CF analytics-engine), privacy (no PII), and caching duration (5min-1h). This goes beyond what annotations provide.

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?

The description is concise with three sentences covering purpose, usage, and behavioral notes. It could be slightly more structured, but it is efficient and front-loaded.

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?

Given the tool's simplicity (1 param, no output schema), the description fully explains inputs, outputs (top tools, packs, volume), and caching behavior. No gaps for an agent to use this tool 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 100% already describing the 'window' enum and its effect. The description adds guidance on selecting shorter vs longer windows, which enhances understanding beyond the 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?

The description clearly states the tool returns top tools, top packs, and total call volume over configurable windows (24h, 7d, 30d). It distinguishes from siblings by focusing on trending usage, not other analysis or 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?

The description lists three specific use cases (discovering hot data sources, confirming canonical choices, alignment checking), providing clear context. It does not explicitly state when not to use or mention alternatives, but the context is sufficient.

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
Disambiguation3/5

Many tools have distinct purposes, but there are multiple ask_pipeworx variants and several Polymarket tools with similar functions, causing potential confusion. Most other tools are clearly differentiated, but the overlap in query and betting tools reduces clarity.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use snake_case (ai_visibility_check), others use descriptive phrases (ask_pipeworx, generate_llms_txt), and some are very short (arrivals). Lengths vary widely, and there is no uniform pattern.

Tool Count2/5

37 tools is excessive for a coherent server; the scope is too broad, spanning transport, data lookups, prediction markets, and utilities. This suggests a lack of focus, making the server feel like a bundled collection rather than a well-scoped toolkit.

Completeness3/5

The server covers multiple domains but lacks depth. London transport tools are partial (e.g., no real-time tube positions), and domains like weather or stock quotes rely on the ask_pipeworx meta-tool rather than dedicated tools. The surface is broad but not comprehensively complete in any area.

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