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Glama

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

A4.7/5.0
Behavior5/5

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

Adds detail beyond annotations: self-aggregating from CF analytics-engine, no PII, caching behavior (5min-1h). Annotations already declare readOnlyHint, openWorldHint, etc., and description aligns.

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?

Efficient, front-loaded with core purpose, then enumerated use cases and technical notes. Every sentence adds value; no filler.

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?

Fully describes inputs (window) and outputs (top tools, packs, volume). Missing output schema is fine given the description. Annotations cover safety. Tool is simple and well-documented.

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 already has full description for window enum. Description adds practical guidance on window interpretation (hot vs steady-state). Enhances without redundancy.

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?

Clear verb and resource: 'Returns the top tools, top packs, and total call volume'. Distinguishes from siblings by focusing on trending usage data from other AI agents.

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 duration trade-offs. No explicit when-not-to-use but context is strong.

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

A3.6/5.0
Disambiguation2/5

Most of the surface is dominated by overlapping meta-tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) plus paired helpers (discover_tools/suggest_questions, ai_visibility_check/scan_competitor_ai_presence), so an agent can easily pick the wrong one. The seven treasury_* tools are clearly distinct, but they are a small island in a much larger ambiguous set.

Naming Consistency3/5

Names are broadly snake_case and family-prefixed (treasury_*, polymarket_*, pipeworx_*), which helps, but the pattern is not consistently verb_noun: ask_pipeworx, bet_research, entity_profile, deep_research, search_within, and recent_changes mix verb, noun, and product-specific naming styles. Within families it is readable, but across the whole set it is inconsistent.

Tool Count2/5

37 tools is too many for a server whose label is 'Treasury Fiscal'; only about six tools are treasury-specific and the rest are unrelated research, betting, memory, and subscription utilities. This is well into the 25+ heavy range and would make tool selection expensive and error-prone.

Completeness2/5

For a Treasury/Fiscal server the surface is thin: debt, receipts, customs duty, average rates, exchange rates, and net cost cover only a slice of Treasury data. Missing obvious components such as daily yield curves, auction calendars/results, federal outlays/spending by agency or function, and tax or appropriations data; the broad ask_pipeworx router softens but does not fill these as first-class tools.