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Glama

W3c

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. First observed

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare safe read-only. Description adds data source (CF analytics-engine), no PII, caching behavior, and aggregation method. 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.

Conciseness5/5

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

Three concise sentences plus bullet points, front-loaded with main purpose, no wasted words.

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 no output schema, description sufficiently explains return (top tools, packs, call volume). Caching and source mentioned. Complete for a simple trending tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only parameter 'window' fully described with enum and semantic guidance. Schema coverage 100%, description adds meaning beyond enum values.

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 'returns', specific resources (top tools, packs, call volume), and differentiated from siblings like discover_tools. Explicit use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Three specific use cases listed, plus guidance on window selection. No alternatives mentioned but context 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

A3.9/5.0
Disambiguation3/5

The three ask_pipeworx variants plus deep_research and validate_claim overlap heavily on the same routing capability — ask_pipeworx_beta is even explicitly identical to ask_pipeworx right now. The polymarket tools (arbitrage/edges/edge_tracker/fill_risk/kalshi_spread) form a second cluster with fuzzy boundaries, and ai_visibility_check vs scan_competitor_ai_presence overlap. However, most other tools (w3c_search, spec, remember/recall/forget, subscribe/unsubscribe) have clear distinct roles.

Naming Consistency3/5

Names are generally descriptive snake_case with recognizable prefix families (ask_pipeworx_*, polymarket_*, w3c_*), but verb usage is inconsistent: passive labels like ai_visibility_check and entity_profile sit alongside imperatives like recall, forget, subscribe, and resolve_. There's no uniform verb_noun or noun_pattern convention across the set.

Tool Count2/5

33 tools is over the heavy threshold, and the count is wildly mismatched to the server's claimed identity: the server is named 'W3c' yet only 2 of 33 tools (w3c_search, w3c_spec) relate to W3C. The remaining 31 form a sprawling Pipeworx data/prediction-market service that would justify its own server, making this aggregation incoherent.

Completeness3/5

For its actual purpose (broad data research + prediction markets), the surface is fairly complete: search, grounded answers, deep research, comparison, entity profiles, entity resolution, memory, subscriptions, and feedback cover the main workflows. But for the server's stated W3C purpose, only search and spec-detail exist with no broader standards tooling. The domain mismatch makes completeness hard to credit.

Resources