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Boi Il

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

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds extra behavioral context: fans out across two services, partial failures degrade gracefully, and bundlephobia's first measurement may take 5-30s. This adds significant value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is a single, well-organized paragraph. It front-loads purpose, then usage, then behavioral notes. Every sentence adds value without redundancy.

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?

Even without an output schema, the description details the return structure (summary fields, advisories, links, alternatives). It covers failure modes and ecosystem scope, making it 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 coverage is 100% with descriptions for both parameters. The description adds context: scoped packages are accepted and version defaults to latest. This enhances the schema descriptions.

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 the tool performs a composite check for npm packages using deps.dev and bundlephobia, specifying the verb 'scan' and resource 'dependency'. It distinguishes from siblings by noting other ecosystems are handled elsewhere.

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 a package. Also states ecosystem limitation (NPM only) and directs other ecosystems to deps.dev:version, providing clear alternatives.

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

A4/5.0
Disambiguation3/5

Most tools have highly detailed descriptions that clarify their distinct roles, and the pipeworx/boi/polymarket families are individually distinguishable. However, ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx (a true duplicate), and the polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) share overlapping purpose and could cause misselection despite their lengthy docs.

Naming Consistency3/5

Many tools follow a clear verb_noun pattern (compare_entities, discover_tools, resolve_entity, validate_claim), but a large subset uses noun-first or prefixed compound names (ai_visibility_check, bet_research, boi_exchange_rate, polymarket_arbitrage). The naming is readable and group-consistent (boi_*, polymarket_*, ask_pipeworx*) but the overall convention is mixed rather than uniform.

Tool Count2/5

At 34 tools, the set exceeds the 25+ threshold for 'too many' and spans many unrelated domains (data lookup, prediction markets, memory, subscriptions, AI visibility, llms.txt generation, feedback). The broad scope explains the count, but many tools feel like add-on utilities rather than a tightly scoped server, making the surface feel bloated.

Completeness4/5

The core domain—authoritative structured data access—is extremely well covered: universal routing, grounded mode, deep research, entity profiles, comparisons, claim validation, resolution, discovery, and suggestions. Minor gaps exist (no explicit tool for fetching a pipeworx:// citation URI directly, no update operation for subscriptions), but agents can work around these via the router and existing subscription lifecycle tools.

Resources