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Ieee Standards

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?

Annotations already provide read-only, open-world, idempotent, non-destructive hints. Description adds crucial behavioral details: partial failures degrade gracefully, bundlephobia first measurement can take 5-30s, and sources_failed will list timeouts. No contradictions.

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 informative and well-structured, starting with purpose, then usage, return details, and limitations. A bit long but every sentence adds value. Front-loaded effectively.

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, description thoroughly details return blocks (summary, advisories, links, alternatives), partial failure behavior, and ecosystem scope. Covers all necessary context.

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%, so parameters are well-documented. Description adds that scoped packages are accepted and version defaults to latest, but this is minor 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 evaluating npm packages, fanning out to deps.dev and bundlephobia. It answers 'should I add this npm package' and covers license, advisories, size, etc. No confusion with sibling tools as they are diverse.

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: 'Use whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me''. Also specifies NPM ecosystem only in v1 and mentions alternatives for other ecosystems.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Ieee Standards toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Several tools blur together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer factual questions with overlapping routing behavior, while polymarket_edges, polymarket_arbitrage, and bet_research all surface prediction-market opportunities. Long descriptions help, but the boundaries between these clusters are genuinely unclear, and the three IEEE tools are buried in a sea of unrelated Pipeworx tools.

Naming Consistency4/5

The naming is predominantly snake_case with clear family prefixes like ieee_, ask_pipeworx_, and polymarket_, and most tools follow a readable verb_noun or noun_verb shape. Minor deviations exist (remember/recall/forget, bet_research, pipeworx_trending) but there is no camelCase/mixed-convention problem, so the overall pattern is predictable.

Tool Count1/5

A server named 'Ieee Standards' exposes 34 tools, yet only three of them (ieee_search, ieee_standard_search, ieee_article) actually serve that domain. The remaining 31 tools form a general Pipeworx data, prediction-market, memory, and subscription platform, which is an extreme scope mismatch for the stated server purpose.

Completeness4/5

For the IEEE lookup domain, the three IEEE tools cover the core read-only workflow: broad corpus search, standards-specific search, and full metadata retrieval by article number or DOI. Minor gaps exist (browsing by committee, revision/status history, full-text access) but those are workable or inherently restricted by IEEE's paywall.

Resources