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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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds valuable context: data source (CF analytics-engine), no PII, and caching durations per window. This goes beyond structured fields.

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?

Two sentences plus a bulleted use-case list. Front-loaded with the core result. Every sentence adds value without redundancy or fluff.

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

Completeness4/5

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

Given only one parameter, rich annotations, and no output schema, the description sufficiently covers what, when, and why. It mentions caching and data source. Minor gap: no description of the output format, but acceptable for a simple trending tool.

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?

The sole parameter 'window' has 100% schema coverage with enum values and descriptions. The description further clarifies that shorter windows surface hot trends while longer windows show steady-state demand, adding semantic meaning.

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 selectable windows. The verb 'returns' and resource 'trending data' are specific and distinct from sibling tools 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?

Three explicit use cases are provided (e.g., 'discovering what data sources are hot for current events'). The description also notes caching behavior and window selection guidance. However, no explicit mention of when not to use this tool or direct comparison with alternatives.

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

A4/5.0
Disambiguation4/5

Tools are mostly distinct with detailed descriptions guiding usage, though some overlap exists between similar query tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research, which could cause confusion for agents not reading carefully.

Naming Consistency3/5

All tool names use snake_case and are readable, but there is no consistent verb-noun pattern. Prefixes vary widely (actions like ask, compare, generate vs. domains like denue, polymarket), making the naming scheme inconsistent.

Tool Count3/5

With 35 tools, the count is high for a server named 'Denue', which suggests a narrower focus. While the breadth may be justified by the platform's capabilities, the number feels slightly heavy and could be streamlined.

Completeness4/5

The tool set covers a wide range of data sources and operations, but it is read-only with no write capabilities for external data. Memory and subscription tools add some action, but overall, it is fairly complete for its stated purpose.