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Google_maps

by io.github.pipeworx-io

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when value was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. sources_used / sources_failed say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit notes line, not a bare failure. type accepts "company" or "ticker" interchangeably — both take the same value shapes above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes"company" or "ticker" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon.
valueYesTicker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna") — names resolve via SEC EDGAR company-name match.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior, and the description adds substantial non-obvious details: the specific sources fanned out, USPTO sunset soft-fail, empty sections meaning real absence of data, resolved:false behavior for private companies, and fallback behavior. 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?

The description is long and dense, but nearly every sentence adds operational value and key instructions are front-loaded with examples. It could be improved with bullets or shorter paragraphs, but the density is justified by the tool's complexity.

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?

With no output schema, the description takes on the burden of explaining return sections: cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and the meaning of sources_used/sources_failed. It also covers edge cases like empty FDA sections and private company resolution, making the call contract fully transparent.

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 coverage is 100%, but the description still adds meaningful semantics: `type` values are interchangeable, `value` can be a ticker, zero-padded CIK, or company name, name resolution happens via SEC EDGAR, and the resolved_from/resolved_to fields are explained. This goes well beyond the schema.

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 states a specific verb and resource: 'full cross-source profile of a US public company in ONE parallel call,' with concrete example phrasings. It also distinguishes the tool from chained single-source lookups by emphasizing the holistic, fan-out behavior.

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?

Provides explicit when-to-use guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies acceptable input forms and what happens for private companies, making the invocation conditions clear.

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

A3.5/5.0
Disambiguation2/5

The tool set mixes unrelated domains (maps, prediction markets, npm dependencies, memory storage) under one server named 'Google_maps'. While individual tool descriptions are clear, an agent cannot easily distinguish which tools belong to the maps domain and which are extraneous, causing confusion about the server's actual purpose.

Naming Consistency2/5

Tool names lack a consistent convention. Maps tools use 'maps_' prefix, but other tools have names like 'ask_pipeworx', 'bet_research', 'forget', etc., mixing prefixes, verb styles, and underscore usage. No unified naming pattern across the set.

Tool Count2/5

37 tools is excessive for a specialized maps server. Only 7 tools are map-related; the remaining 30 cover disparate domains (financial data, prediction markets, system utilities), making the server seem like a random collection rather than a focused integration.

Completeness2/5

For a maps server, common operations like static map generation, place photos, or timezone lookups are missing. The inclusion of many non-maps tools creates a 'kitchen sink' effect, undermining completeness for the stated purpose. The tool surface is severely incomplete if judged by the server name.

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