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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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds caching duration (5min-1h), privacy (no PII), and derivation from CF analytics-engine. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with core functionality. Second sentence lists use cases. Slightly wordy but every sentence serves purpose (caching, privacy, window guidance). Could be trimmed but acceptable.

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 single optional param, no output schema, and low complexity, description fully covers purpose, behavioral traits, parameter guidance, and use cases. 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 the parameter fully (enum, description). Description adds semantics: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' 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?

Description clearly states it returns top tools, top packs, and total call volume over a chosen window. Distinct from siblings like 'discover_tools' or 'subjects' by focusing on trending usage 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?

Lists three specific use cases (discovering hot data sources, confirming canonical tool, aligning use case) and explains window trade-offs. Lacks explicit when-not-to-use or alternatives, but use cases are clear.

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

Most tools have clearly distinct purposes, but several overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (only differing in verification/depth), and polymarket_edges / polymarket_arbitrage / polymarket_edge_tracker / polymarket_fill_risk / polymarket_kalshi_spread all target similar prediction-market signals, which could cause mis-selection without careful reading.

Naming Consistency4/5

Most names follow a clear verb_noun pattern (resolve_entity, query_table, remember, recall, forget, subscribe, unsubscribe, validate_claim, compare_entities, search_within), but there are exceptions like ai_visibility_check (adjective_noun), generate_llms_txt (verb_noun with dot), and several polymarket_* names that are fine but inconsistent with the snake_case verb-first convention.

Tool Count5/5

35 tools is a large but reasonable surface for a broad data/serach platform covering company financials, economics, prediction markets, memory, subscriptions, and discovery. The count is justified by the wide domain, and the set is not bloated with trivial duplicates.

Completeness4/5

The surface covers core CRUD for entities (resolve, profile, compare, search, query) and memory (remember/recall/forget), plus subscriptions and meta-tools. Minor gaps: no explicit tool for updating/creating entities (understandable for a read-only data service), and no tool for listing all available table schemas beyond discovery (subjects covers this). Overall strong coverage.

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