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Glama

Weather Gc Ca

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

A4.4/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral details beyond annotations: it explains the composite fan-out nature, potential 5-30s delay on new versions for bundlephobia, and graceful partial failure handling with sources_failed reporting. 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?

The description is slightly verbose but front-loads the core purpose. It lists return fields and constraints in a block, which is informative but could be more structured. Most sentences earn their place, though the return field enumeration could be formatted more concisely.

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?

Despite no output schema, the description comprehensively lists all return components (summary block, per-advisory detail, links, alternative versions). It covers edge cases like partial failures, timeouts, and ecosystem limitations. This is well-rounded and complete for the tool's complexity.

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 coverage is 100% with both parameters well-described. The description adds context beyond schema: it mentions that scoped packages are accepted for the 'package' parameter and that 'version' defaults to the latest when omitted. This adds meaningful information 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?

The description clearly states it's a composite check for npm packages, combining deps.dev and bundlephobia. It specifies the exact purpose: answering questions about safety, popularity, and size. It distinguishes itself from siblings by explicitly limiting to NPM ecosystem and mentioning alternatives for other ecosystems.

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?

The description explicitly says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also notes the NPM-only scope and graceful degradation, providing clear context for when to use. It could be improved by explicitly stating when not to use, but the context suffices.

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

A3.8/5.0
Disambiguation3/5

Many tools have distinct purposes (e.g., current_observations vs. climate_daily), but several query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, bet_research) overlap in function, all routing questions to a large tool catalog. This can confuse an agent about which to use.

Naming Consistency3/5

Names are snake_case but follow no consistent pattern: some are verb_noun (ask_pipeworx), some noun_adjective (climate_daily), others compound (ai_visibility_check). The mix is readable but not predictable.

Tool Count2/5

33 tools is high for a server named 'Weather Gc Ca', which implies a focused weather service. Many tools are unrelated to weather (Polymarket, SEC, FDA, etc.), making the count inflated and mismatched to the server's apparent scope.

Completeness2/5

For weather, the server covers alerts, current observations, and climate records but lacks forecasts, radar, satellite imagery, and station listings. While the broader Pipeworx catalog is extensive, the weather-specific surface is incomplete for a dedicated weather tool.

Resources