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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

A4.8/5.0
Behavior5/5

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

Description adds behavioral details beyond annotations: fans out across two sources, partial failures degrade gracefully, bundlephobia may take 5-30s, and sources_failed is listed if timeout. 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?

Description is front-loaded with purpose and is structured logically, but is somewhat verbose (multiple sentences). Still, every sentence adds value, so no waste.

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 fully explains return format (summary block fields, per-advisory detail, links, alternative versions) and error handling (partial failures). Given tool complexity with 2 params and no output schema, it is complete.

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 covers 100% of parameters, so baseline is 3. Description adds value by clarifying that scoped packages (e.g., "@types/node") are accepted for 'package' and that 'version' defaults to latest when omitted.

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 a specific verb and resource: 'Composite check for evaluating whether to add an npm package'. It distinguishes itself from siblings by specifying NPM-only and mentioning alternatives like deps.dev:version 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 Guidelines5/5

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

Explicitly says 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"' and identifies limitations: 'NPM ecosystem only in v1; PyPI/Maven/Cargo/Go fall under deps.dev:version directly.'

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
Disambiguation3/5

Tool purposes are largely distinct across domains (Jira, data queries, prediction markets), but there is overlap within domains, e.g., ask_pipeworx vs ask_pipeworx_grounded and multiple Polymarket edge analysis tools.

Naming Consistency2/5

Naming mixes multiple conventions: jira_ prefix, pipeworx_ prefix, polymarket_ prefix, and plain verbs (remember, forget, recall). No consistent pattern across the entire set.

Tool Count2/5

34 tools is excessive for a server named 'Jira' which only has 4 Jira-specific tools. The majority are unrelated Pipeworx and Polymarket tools, making the scope bloated.

Completeness2/5

Jira-specific tools are incomplete (missing create, update, delete). While Pipeworx and Polymarket tools are comprehensive, they are out of place for a Jira server, leaving gaps in its stated purpose.

Resources