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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=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: caching (5min-1h), self-aggregating, no PII, source from CF analytics-engine. No contradiction with 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, front-loaded with core purpose, then use cases, then technical details. No redundant or wasted words.

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?

For a simple tool with 1 optional parameter and no output schema, the description explains return values conceptually, caching, and source. Lacks explicit format but sufficient given annotations cover safety.

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 one parameter described. Description adds guidance: 'Shorter windows surface what's hot right now; longer windows show steady-state demand' and notes the default '24h', enriching the schema's enum description.

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 verb 'Returns' and specifies the resources: 'top tools, top packs, and total call volume' over a window. It distinguishes this tool from siblings like 'ask_pipeworx' and 'discover_tools' by focusing on trending/aggregate data.

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 specific use cases are listed (discovering hot data sources, confirming canonical tool, aligning use case). Window parameter guidance explains when shorter/longer windows are appropriate. No explicit when-not-to-use, but the context is clear enough.

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

The set mixes Salesforce CRUD tools with a large Pipeworx research and prediction-market platform, and several tools overlap heavily: ask_pipeworx vs ask_pipeworx_beta are functionally identical, grounded/validate_claim/deep_research cover similar lookup/verification territory, and the six polymarket/bet tools share edge-finding purposes with only subtle distinctions. An agent would need to read long descriptions carefully to pick the right one, so misselection risk is high.

Naming Consistency3/5

Salesforce tools follow a clear sf_verb_noun pattern, and the Pipeworx tools mostly use lowercase snake_case phrase names, but the conventions diverge: ask_pipeworx has no underscore, deep_research/entity_profile are noun phrases rather than verb-first, and the sf_* prefix is a separate naming family. It is still readable, but it is not a single predictable pattern.

Tool Count2/5

39 tools is well past the heavy threshold, and most belong to a broad data/research platform rather than the Salesforce scope implied by the server name; only 8 tools are actually Salesforce CRUD/query operations. The count feels bloated for a coherent assistant, even if individual features are useful.

Completeness4/5

The Salesforce subset is complete: create/get/update/delete/query/search/describe/list-object cover the record lifecycle with no dead ends. The broader Pipeworx ecosystem also has strong coverage, including routing, grounded verification, research, entity resolution, memory, and subscriptions, with only minor gaps such as no direct citation-fetch tool and no Salesforce upsert/bulk operations.