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Glama

Tradier

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description goes beyond: 'Partial failures degrade gracefully', 'bundlephobia's first measurement on a new version can take 5-30s', and mentions 'sources_failed' list. 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?

The description is dense but front-loaded with the purpose. It uses one long paragraph which could be more structured, but every sentence is informative and earns its place.

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 the composite nature, no output schema, and rich annotations, the description is extremely complete: explains return structure (summary block, advisories, links, alternatives), partial failure, ecosystem limitations, and timing caveats.

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

Parameters5/5

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

Schema covers both parameters (package, version) with descriptions. The description adds clarity: 'Scoped packages (e.g. "@types/node") are accepted' and 'Defaults to the latest published version when omitted.'

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 composite purpose: checking if an npm package should be added to a project, using deps.dev and bundlephobia. It specifies the verb ('check'), resource (npm package), and distinguishes from siblings (e.g., 'NPM ecosystem only in v1').

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 tells when to use: 'whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' Also provides exclusions: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly.'

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

Multiple tools share overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and the five polymarket_* tools cover heavily overlapping territory. An agent must read lengthy descriptions to distinguish between them, and pairs like validate_claim vs ask_pipeworx_grounded or discover_tools vs suggest_questions have fuzzy boundaries.

Naming Consistency2/5

Naming is wildly inconsistent: verb_noun (compare_entities, discover_tools), bare verbs (forget, remember, subscribe), noun phrases (entity_profile, recent_alerts, pipeworx_feedback), prefixed families (tradier_*, polymarket_*) and suffixed variants (ask_pipeworx_beta, ask_pipeworx_grounded). There is no single predictable convention across the set.

Tool Count2/5

34 tools is far beyond the 15-25 heavy range, and the count is inflated by near-duplicates like ask_pipeworx/ask_pipeworx_beta and five polymarket edge tools. The server mixes several unrelated domains (Tradier quotes/options, Pipeworx research, Polymarket analysis, memory, subscriptions, web utilities), making the scope feel unbounded.

Completeness2/5

For a server named Tradier, having only quote and option-chain endpoints is a significant gap—no historical data, account, positions, or order execution. The Pipeworx/Polymarket side is more complete, but the inclusion of unrelated utilities like generate_llms_txt and scan_dependency means no single domain is fully served.

Resources