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Glama

Geoboundaries

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.

Schema Changelog

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

  1. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. Only \"company\" supported today; person/place coming soon."New value: +"\"company\" or \"ticker\" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "ticker"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker (e.g., \"AAPL\") or zero-padded CIK (e.g., \"0000320193\"). Names not supported — use resolve_entity first if you only have a name."New value: +"Ticker (e.g., \"AAPL\"), zero-padded CIK (e.g., \"0000320193\"), or company name (e.g., \"Moderna\") — names resolve via SEC EDGAR company-name match."
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already mark read-only, idempotent, and non-destructive, so the description's extra behavior color is valuable: parallel fan-out across EDGAR, XBRL, USPTO, USAspending, FDA, DOL, GDELT, and GLEIF; soft-fail for the USPTO sunset; empty sections meaning genuine no-data; sources_used/sources_failed; and resolved:false with notes for private companies. This goes well beyond the hints.

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, but at least one dense introductory sentence captures the core purpose and preference. The subsequent detail about return sections and failure modes earns its place because this tool has many sources and edge cases. Slight deduction for being a dense wall of text without structural separation.

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 carries full responsibility for explaining results, and it does: it lists every return section (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/failed) and explains expected empties and fallbacks. For a 2-parameter tool, nothing needed to call it correctly is missing.

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% and the schema descriptions already explain the interchangeable type, the allowed value shapes, examples, and name resolution via SEC EDGAR. The tool description largely restates those param details, so it adds little new parameter-level meaning beyond what the schema already provides.

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?

States a specific verb ('profile') and resource ('US public company'), anchored by many concrete user phrasings and a clear one-line summary: 'full cross-source profile of a US public company in ONE parallel call.' It also differentiates from chaining single-source lookups and implicitly from siblings like compare_entities and resolve_entity.

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 says when to prefer this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It then details accepted value forms (ticker, CIK, name) and the graceful private-company path, giving an agent enough guidance to decide and execute.

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

A3.8/5.0
Disambiguation2/5

Many tools have overlapping or unclear purposes, e.g., multiple entity research tools (entity_profile, recent_changes, compare_entities, validate_claim) and several betting tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread). The memory tools (remember, recall, forget) and generic lookup tools (ask_pipeworx, discover_tools) further blur boundaries, making it hard for an agent to consistently select the right tool.

Naming Consistency2/5

Tool names follow no consistent pattern: some use snake_case verbs (forget, recall, remember), others are noun phrases (entity_profile, recent_changes), and many have mixed conventions (ai_visibility_check, ask_pipeworx, bet_research). There is no clear verb_noun structure, and the naming style varies widely across the set.

Tool Count3/5

At 22 tools, the count is within a reasonable range, but the server's stated purpose ('Geoboundaries') is severely mismatched with the actual tool set, which covers data retrieval, betting, memory, and more. The number is not excessive for the breadth of functionality, but it feels bloated for a server that should be focused on geographic boundaries.

Completeness1/5

The server is named 'Geoboundaries' but only provides two boundary-related tools (get_boundaries, get_geometry). The remaining 20 tools are unrelated, covering general data access, betting arbitrage, and memory operations. This leaves massive gaps for the implied domain (no tools for boundary editing, search by location, or other geographic operations) while over-supplying tools for unrelated tasks.

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