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Glama

Landprice

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

A5/5.0
Behavior5/5

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

Discloses behavioral traits beyond annotations: fans out to external services, partial failures degrade gracefully, bundlephobia first measurement latency up to 30s, and sources_failed list. No contradiction with readOnlyHint, openWorldHint, idempotentHint, destructiveHint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single paragraph front-loaded with purpose, no wasted sentences. Each sentence adds distinct value: composite nature, data sources, usage cues, ecosystem scope, behavior notes.

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 explains return structure (summary block, advisories, links, alternatives) and handles edge cases (partial failures, latency). Complete for agent decision-making.

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?

Adds meaning beyond input schema: accepts scoped packages, version defaults to latest. Schema coverage is 100%, and description enriches parameter understanding.

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 tool's purpose as a composite check for adding an npm package, listing specific data sources (deps.dev, bundlephobia) and what they provide. It distinguishes itself from sibling tools, none of which are package evaluation.

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 guidance on when to use (agent asks about package safety/popularity/size) and when not (non-npm ecosystems), with an alternative suggested (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.

All Landprice toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tool clusters have unclear boundaries. `ask_pipeworx_beta` is explicitly described as currently identical to `ask_pipeworx`, `discover_tools` overlaps with `suggest_questions`, and the six Polymarket tools (`bet_research`, `polymarket_edges`, `polymarket_arbitrage`, etc.) blur together for opportunity-finding. An agent would struggle to pick the right tool without reading every description carefully.

Naming Consistency4/5

Naming is overwhelmingly consistent snake_case with a verb_noun or noun pattern (`ask_pipeworx`, `list_subscriptions`, `validate_claim`, `recent_changes`). The `polymarket_*` and `ask_pipeworx_*` families follow clear conventions. Minor deviations like `bet_research`, `entity_profile`, and `landprice_points` being noun-first are still readable and predictable.

Tool Count2/5

32 tools is heavy for a server named 'Landprice' when exactly one tool (`landprice_points`) actually concerns land prices. The vast majority of tools constitute an unrelated general-purpose data research and prediction-market platform, making the count feel bloated and scattershot relative to the server's stated purpose.

Completeness3/5

For the actual broad scope revealed by the tools — structured data lookup, grounded verification, deep research, entity resolution, comparison, monitoring, and memory — the surface is reasonably complete with no obvious dead ends. However, for the 'Landprice' domain implied by the server name, coverage is nearly absent: only Japan is covered, with no other countries, address search, or property-level data.

Resources