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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?

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. Description adds critical behavioral details: partial failures degrade gracefully, bundlephobia first measurement can take 5-30 seconds, and sources_failed will list timed-out sources. 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 dense but well-structured. It front-loads the core purpose and then lists details. Could be slightly more concise but effectively uses space.

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 thoroughly lists return fields (summary block with specific metrics, per-advisory detail, links, alternative versions). Covers edge cases (partial failures, timing). Highly complete for a composite tool.

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 both parameters with clear descriptions (package name, optional version). Description adds context: version defaults to latest, scoped packages accepted. This adds slight value beyond schema.

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 it is a composite check for npm package evaluation combining deps.dev and bundlephobia. It explicitly names the resources (license, advisories, version history, bundle size) and distinguishes from siblings by being npm-specific and composite.

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 states when to use: when an agent asks about safety, popularity, size, or cost of adding an npm package. Also notes NPM-only in v1 and directs users to deps.dev:version for other ecosystems.

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

A4.1/5.0
Disambiguation3/5

Most tools have strong, detailed descriptions with explicit usage guidance, but a few clusters are genuinely ambiguous: ask_pipeworx_beta is currently an exact duplicate of ask_pipeworx, and the Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker) overlap heavily in purpose. The descriptions help differentiate them, but an agent could still easily select the wrong variant.

Naming Consistency4/5

All tool names are snake_case and most follow an imperative verb-first pattern such as resolve_entity, subscribe, or validate_claim. A few noun-style names like entity_profile, bet_research, and interaction_count deviate, but the consistent underscore style and clear prefixes like polymarket_ and pipeworx_ keep the set predictable.

Tool Count2/5

At 33 top-level tools, the surface is heavy, and several tools are near-duplicates or narrow variants of the same core capability. The broad scope explains some of the count, but the agent-facing API would be cleaner with fewer, more consolidated entry points.

Completeness5/5

The set provides strong lifecycle coverage for its main workflows: querying and grounding, deep research, entity resolution, company profiling, comparisons, Polymarket edge analysis with fill-risk checks, memory storage, and subscription management. There are no obvious dead ends that would prevent an agent from completing a typical task.