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Montreal Events

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.

TDQS

A4.4/5.0
Behavior4/5

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

Description adds detail beyond annotations: data derived from CF analytics-engine, no PII, cached 5min-1h. Annotations already indicate read-only, idempotent, non-destructive. No contradiction.

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?

Paragraph-style but each sentence adds value (three use cases, caching, no PII). Slightly verbose but 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?

For a simple 1-param tool with no output schema, description covers return value, data source, caching, use cases. Fully adequate.

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 has 1 parameter with enum; description adds semantic guidance on window choice ('hot right now' vs 'steady-state demand'). Coverage 100% gives baseline 3, description elevates it.

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 verb 'returns', resource 'top tools, top packs, and total call volume', and scope 'over a recent window'. It uniquely identifies the tool among siblings as a trending data source.

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 choice, aligning use case) and explains window selection. Lacks explicit when-not-to-use or alternatives but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Montreal Events toolsInspect
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TDQS

B3.4/5.0
Disambiguation2/5

The set contains multiple near-duplicate meta-query tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools) and five overlapping Polymarket analysis tools, creating genuine selection ambiguity despite detailed descriptions. The single events tool is distinct, but it is drowned out by a crowd of similar data-research utilities.

Naming Consistency4/5

Almost all tools follow a consistent lowercase snake_case verb_noun pattern (ask_pipeworx, compare_entities, validate_claim, remember, forget). Only 'events' deviates by being a bare noun, but the overall convention is predictable and readable.

Tool Count1/5

32 tools is extreme for a server named 'Montreal Events', and only one tool actually relates to that domain. The remaining 31 form a sprawling, unrelated data-research, prediction-market, and memory toolkit that would overwhelm any agent trying to work with Montréal event data.

Completeness1/5

For the server's stated purpose, the surface is severely incomplete: a single read-only event search with no event details, venue info, categories, or management operations. The Pipeworx tools may cover their own domain thoroughly, but they contribute nothing to the Montreal Events scope.

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