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Montreal Events

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

TDQS

A4.6/5.0
Behavior5/5

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

Discloses important behavioral details beyond annotations: first bundlephobia measurement takes 5-30s, partial failures degrade gracefully, and sources_failed lists timeouts. 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.

Conciseness4/5

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

The description is thorough but not overly verbose. It front-loads the core purpose and uses bullet-like structure for return values. Could be slightly tightened, but each sentence adds value.

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 the tool's complexity (multiple sources, timing, partial failures), the description covers all necessary context: output fields, behavior on failure, ecosystem scope, and version handling. No output schema exists, so the explanation of return values is sufficient.

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

Parameters3/5

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

Parameter schema coverage is 100%, so the description adds little beyond what is already documented. It repeats acceptance of scoped packages and default version, which are in the schema. No additional semantics.

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 it is a composite check for npm packages using deps.dev and bundlephobia, specifying the exact purpose and distinguishing it from sibling tools via ecosystem and composite nature.

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?

Explicitly says when to use: when an agent asks about safety, popularity, size, or cost of adding an npm package. Also gives exclusion: NPM only in v1, with alternatives for other ecosystems.

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.

Resources