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Macro Snapshot

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?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds key behavioral traits: fans out across two services, partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed will list timeouts.

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 detailed but front-loaded with the composite nature. Though slightly long, every sentence provides necessary information 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?

Given no output schema, the description lists all return fields (summary block, per-advisory detail, links, alternative versions) and explains partial failure behavior. It is comprehensive 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 descriptions for both parameters. The description adds value by noting that scoped packages are accepted and that version defaults to latest, providing additional context beyond the 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?

The description clearly states it's a composite check for npm packages covering license, advisories, version history, bundle size, and tree-shaking support. It is distinct from sibling tools, none of which focus on package scanning.

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 package safety, popularity, or cost. Also clarifies it's NPM-only in v1 and mentions fallback to deps.dev 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

A3.9/5.0
Disambiguation3/5

Several clusters overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions, and ai_visibility_check duplicates scan_competitor_ai_presence at a smaller scale. The detailed descriptions do separate most of these by routing, mode, or output, but the currently identical beta router and the broad ask/research family create real ambiguity.

Naming Consistency3/5

Names are all lowercase snake_case and there are coherent prefixes like polymarket_ and pipeworx_, but the set mixes imperative verb_noun names (list_subscriptions, validate_claim) with descriptive noun phrases (macro_snapshot, entity_profile, polymarket_edge_tracker) and bare verbs. The inconsistency is readable but not a single predictable pattern.

Tool Count2/5

33 tools is well beyond the 25+ threshold for a coherent server, and the set spans many unrelated domains: data routing, prediction markets, memory, subscriptions, AI visibility, package scanning, and llms.txt generation. Even if each cluster has a purpose, the server is overloaded and several high-level wrappers could be consolidated.

Completeness4/5

The main clusters are well covered: memory has remember/recall/forget, subscriptions have subscribe/list/recent_alerts/unsubscribe, and company research has resolve_entity, entity_profile, recent_changes, and compare_entities. Minor gaps exist (no direct trade placement, no general web search, no account/profile management), but agents can complete most workflows without dead ends.

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