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Glama

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

A4.8/5.0
Behavior5/5

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

The description goes far beyond the readOnly/openWorld/idempotent annotations by detailing the fan-out across SEC EDGAR, XBRL, USPTO, USAspending, Purple Book, DOL LCA, GDELT/GNews, and GLEIF. It also explains sources_used/sources_failed semantics, fallbacks, and empty-section behavior, giving the agent a rich model of what will happen.

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 front-loaded with purpose and usage, but it is a long, dense paragraph with several parenthetical asides. Still, every clause carries operational value, especially given the absence of an output schema, so the length is largely justified.

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 fully compensates by enumerating all returned sections, including recent_filings URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, and LEI. It also covers failure modes and expected empty results, leaving little ambiguity for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful extras: concrete examples for tickers, CIKs, and company names, zero-padded CIK convention, resolved_from/resolved_to behavior, and the private-company edge case. It does repeat some schema text, but the added examples and resolution semantics justify the bump.

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 exactly what the tool produces: a 'full cross-source profile of a US public company in ONE parallel call.' It opens with concrete user utterances and explicitly distinguishes itself from single-pack SEC/XBRL/news lookups, making the tool's purpose unmistakable.

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?

The description gives an explicit directive: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also clarifies the accepted input forms and how private companies are handled, which helps an agent decide when this tool is appropriate.

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

The tool set mixes tools from multiple unrelated domains (HathiTrust, Pipeworx data platform, Polymarket, npm, etc.), making it unclear which tool to use for a given task. Overlap exists between ask_pipeworx and ask_pipeworx_grounded, and between several Polymarket tools, while the HathiTrust-specific tools are few and buried among many others, causing confusion.

Naming Consistency2/5

Naming conventions are inconsistent across the tool set. Some tools use verb_noun (check_full_view, lookup_by_identifier), others use noun_verb (entity_profile, deep_research), and some are single verbs (forget, remember, subscribe). There is no predictable pattern, making it harder for an agent to guess tool names.

Tool Count1/5

With 33 tools, the count is high, but only 3 (get_record, lookup_by_identifier, check_full_view) are relevant to the server's stated purpose (HathiTrust). The remaining 30 tools appear to be from unrelated domains (Pipeworx data platform, Polymarket, npm, etc.), making the tool count severely mismatched with the server name.

Completeness2/5

For the HathiTrust domain, the tool surface is severely incomplete: only three basic lookup tools with no search, browse, or management capabilities. The broader set includes tools for many other domains, but that does not compensate for the lack of coverage of the server's primary purpose.