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Glama

Osha

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 provide readOnly/openWorld/idempotent hints. Description adds critical behaviors: composite call, partial failure handling, bundlephobia latency (5-30s), sources_failed list. 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?

Single dense paragraph but well-organized, listing return fields in a readable manner. Could benefit from bullet formatting but remains efficient and informative.

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?

No output schema, but description fully details return structure (summary block, per-advisory, links, alternate versions). Covers ecosystem limitation, error handling, and expected latency. Complete 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 covers 100% of parameters. Description adds value by noting scoped packages are accepted and version defaults to latest, going beyond 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?

Clearly states it's a composite check for npm packages covering license, advisories, version history, bundle size, etc. Distinguishes from sibling tools by specifying NPM-only scope and composite nature.

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 'is X safe / popular / small' or 'what does adding lodash cost me'. Also specifies NPM only and points to 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.

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TDQS

A4.1/5.0
Disambiguation3/5

Several tools have similar purposes, such as the four ask_pipeworx variants and multiple prediction market analysis tools (bet_research, polymarket_edges, polymarket_arbitrage, etc.). While descriptions clarify differences, the overlap could cause misselection by an agent, especially with the high number of specialized market tools.

Naming Consistency4/5

All tool names use snake_case, but the pattern is not fully consistent: some start with verbs (ask_pipeworx, bet_research, compare_entities) while others are noun phrases (entity_profile, recent_alerts, osha_search). This minor inconsistency does not severely hinder readability.

Tool Count3/5

33 tools is on the high side, but the server acts as a comprehensive data gateway covering multiple domains (financials, prediction markets, OSHA, etc.) and includes meta-tools (memory, subscriptions, feedback). The count is justified by the breadth, though it borders on being overwhelming.

Completeness4/5

The tool set covers core workflows: data lookup (ask_pipeworx), entity profiles, comparisons, prediction market analysis, and memory management. There are minor gaps, such as no direct SEC filing retrieval tool (handled via ask_pipeworx), but the overall surface is comprehensive for the server's stated purpose.

Resources