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Glama

Idigbio

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

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations: it explains fan-out to two external services, mentions potential slow first measurement for bundlephobia (5-30s) and graceful degradation via 'sources_failed'. This is especially valuable as the agent needs to set expectations for latency and partial results.

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 a single dense paragraph, front-loading the core purpose and then detailing components. It is relatively concise for the amount of information (purpose, components, usage, ecosystem, edge cases). A slight improvement could be using bullet points for the return fields, but it remains effective.

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, the description enumerates all return fields (summary block fields, per-advisory, links, alternative versions) and covers edge cases (partial failures, timeout behavior). It also clarifies ecosystem limitations and boundaries, making the tool self-contained for the agent.

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 detailed descriptions for both parameters. The description adds minor extra context (e.g., 'Scoped packages are accepted') but does not substantially enhance the parameter understanding beyond the input schema. Baseline of 3 is appropriate given high schema coverage.

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 is a composite check for adding an npm package, specifying it fans out across deps.dev and bundlephobia. It directly addresses the user's question 'should I add this npm package', which distinguishes it from sister tools like 'scan_competitor_ai_presence' or 'validate_claim'.

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?

Explicit usage guidance is provided: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also limits scope to 'NPM ecosystem only in v1' and mentions alternatives for other ecosystems, helping the agent decide when not to use this tool.

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

A3.6/5.0
Disambiguation2/5

Several tools route to the same underlying Pipeworx engine (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research), and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) and the entity-investigation tools (entity_profile, compare_entities, recent_changes, resolve_entity) also have heavily overlapping purposes that an agent could easily confuse.

Naming Consistency3/5

Most tools use snake_case, but the set mixes verb-first names (get_specimen, search_specimens, resolve_entity, validate_claim) with noun-first names (entity_profile, recent_alerts, polymarket_edges, pipeworx_trending). The polymarket_ and pipeworx_ prefixes give some internal consistency, but the overall pattern is not uniform.

Tool Count2/5

34 tools is heavy for a server named Idigbio, especially since only 3 of the 34 tools (count_by_field, get_specimen, search_specimens) actually relate to iDigBio specimen data. The remaining 31 are a sprawling Pipeworx/prediction-market/marketing/memory toolkit, making the tool count mismatched with the server's apparent identity.

Completeness3/5

The Pipeworx side is quite complete: querying, grounded answers, deep research, entity profiles, comparisons, claim validation, subscriptions, memory, and feedback are all present. However, the iDigBio side, which the server name advertises, is only minimally covered with search/get/count and lacks any collection or media download operations, so the overall surface has notable gaps relative to the server's stated focus.

Resources