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Transport Feeds

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

A4.6/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint), description adds crucial behavioral details: fans out across two services, bundlephobia's first measurement takes 5-30s, partial failures degrade gracefully with sources_failed listing, NPM-only scope. 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 data sources, then usage, return values, limitations, and failure handling. Every sentence adds value, though slightly long. Minor trimming could improve conciseness.

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?

For a composite tool with no output schema, description fully covers inputs, outputs (summary block, advisories, links, versions), failure modes, timing, and scope. Complete for informed usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for both parameters. Description adds little beyond schema, e.g., explaining defaults and scoped packages, but schema already covers these. Baseline 3 is appropriate.

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 the composite purpose: checking npm packages for license, advisories, version history, bundle size, and tree-shake support. It names data sources (deps.dev, bundlephobia) and differentiates from sibling tools like scan_competitor_ai_presence.

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 asked 'is X safe/popular/small' or 'what does adding lodash cost me'. Also tells when not to use: for non-npm ecosystems, use deps.dev:version directly. Provides guidance on partial failures and timing.

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

A3.7/5.0
Disambiguation2/5

There is substantial overlap among the many question-answering tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, compare_entities, entity_profile, recent_changes) and the prediction-market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). While each has nuanced differences, agents will struggle to select the right one, especially with several 'ask_pipeworx' variants that behave nearly identically.

Naming Consistency3/5

Most tool names use snake_case, but patterns vary widely: some are verb_noun (list_feeds, read_feed, subscribe, unsubscribe, remember), others are noun_phrases (polymarket_arbitrage, pipeworx_trending, entity_profile), and a few like 'ask_pipeworx' and 'bet_research' don't follow a consistent structure. The mixed conventions make prediction of new tool names difficult.

Tool Count2/5

With 34 tools, this is far too many for a server named 'Transport Feeds'. The majority of tools are unrelated to transport feeds, covering generic data research, prediction markets, and memory utilities. The count overwhelms any focused purpose and would require extensive discovery to navigate.

Completeness3/5

For the actual data-research and prediction-market functions, the surface is quite complete—covering lookups, comparisons, grounded verification, arbitrage scans, fill risk, trending, and subscriptions. However, for the declared domain (transport feeds), there are only two feed-specific tools (list_feeds, read_feed) with no write/update/delete operations, leaving obvious gaps.

Resources