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Package Market Search

estimate_market
Read-onlyIdempotent

Search npm or PyPI to estimate how crowded a package category is before you claim that a market is empty, niche, or competitive. Use this when you have a category or search phrase such as 'edge orm' and want live result counts plus representative matches. Do not use it to compare exact known package names or to infer adoption from downloads; it reflects search results, not market share. Registry responses are cached for 5 minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesShort registry search phrase to evaluate, for example 'mcp memory server' or 'edge orm'.
registryNoRegistry to search. Use 'npm' for JavaScript ecosystems and 'pypi' for Python ecosystems.npm

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch phrase that was evaluated.
registryYesRegistry that was searched.
topResultsYesRepresentative top search matches that help interpret the market count.
totalResultsYesTotal number of matching packages reported by the registry search.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, and non-destructive. The description adds valuable behavioral context: responses are cached for 5 minutes, and results reflect search relevance not market share, which complements the annotations without contradiction.

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?

Four concise sentences deliver purpose, usage, exclusions, and caching behavior with no filler. The most important information is front-loaded in the first sentence.

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?

For a two-parameter read-only search tool with an output schema and rich annotations, the description covers key behaviors, limitations, and cache behavior. It is fully adequate for an agent to select and invoke the tool correctly.

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 descriptive text for both query and registry. The description itself adds only an example phrase ('edge orm') and reiterates the npm/PyPI choice, providing no additional semantic value beyond the schema, so baseline 3 applies.

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 the tool searches npm or PyPI to estimate package category crowdedness before making market claims. This is a specific verb-resource-purpose combination that distinguishes it from sibling tools focused on compliance, endpoints, pricing, and monitors.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use it ('when you have a category or search phrase') and what not to use it for ('Do not use it to compare exact known package names or to infer adoption from downloads'). However, it does not name a specific alternative tool, slightly reducing the guidance completeness.

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

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there are several lightly overlapping pairs (check_endpoint/preflight_endpoint, check_pricing/compare_pricing_pages, estimate_market/compare_competitors, test_hypothesis/verify_claim). The detailed descriptions and explicit 'do not use for' notes mitigate confusion, so misselection is unlikely.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern (e.g., check_endpoint, create_monitor, verify_claim). Even compound verbs like preflight_endpoint and run_monitor_now adhere to the same structure, making the naming fully predictable.

Tool Count4/5

19 tools is slightly heavy but reasonable for the broad scope covering endpoint checks, pricing, compliance, package research, claim verification, and monitor lifecycle. Each tool has a distinct role, though the count edges close to the 'heavy' range.

Completeness4/5

Core workflows are well-covered: create/list/delete/get/run/preview monitors, single and comparative pricing checks, endpoint and security verification, and claim testing. Minor gaps exist, such as no update_monitor tool or a way to explicitly verify a claim without pre-supplied evidence URLs, but these are workable.

Resources