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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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint:false. The description goes beyond those by explaining cross-source fan-out, the meaning of `sources_used`/`sources_failed`, that an empty section is expected ('real no data, not a bug'), and that unresolved private companies return a structured `resolved:false` with a notes line rather than a bare failure. This is substantial behavioral context not present in 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, but it is purposefully dense: it starts with representative user phrases, states the preference rule, lists all return groups, explains source success/failure semantics, and covers input variations. Each sentence adds relevant operational detail, though the opening example run-on could be tightened without losing meaning.

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 to rely on, the description carries the full burden of explaining what the agent will get back: cik/company_name, resolution metadata, up to 5 filings with URIs, fundamentals, and each auxiliary source, plus the all-important `sources_used`/`sources_failed` distinction and private-company behavior. This is enough for an agent to call the tool correctly and interpret results.

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 description coverage is 100%, so the schema already fully documents `type` and `value`, including the interchangeability of 'company' and 'ticker' and the accepted value shapes. The description confirms this but adds little beyond the schema; the only mild addition is clarifying that name resolution goes through SEC EDGAR's company-name match, which the schema also states.

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 opens with concrete example queries and then states the core function: 'full cross-source profile of a US public company in ONE parallel call.' It clearly names the resource (SEC EDGAR, XBRL, patents, contracts, etc.) and differentiates itself from chaining single-pack lookups, making it easy to distinguish from siblings.

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 explicitly tells the agent when to prefer this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also states what inputs are accepted, mentions that private companies return a non-failure fallback, and notes that person/place support is 'coming soon,' effectively scoping the tool to US public companies.

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

A3.9/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions to data sources with minor differences. Form D tools and meta-tools (discover_tools, suggest_questions) further blur boundaries, making it hard for an agent to select the right tool.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (e.g., resolve_entity, validate_claim, subscribe). However, there are minor deviations like bet_research and deep_research without clear verbs, and the ask_pipeworx variants use irregular suffixes.

Tool Count2/5

With 39 tools, the server is over-scoped, including many utility and meta-tools (remember, recall, forget, list_subscriptions) that inflate the count beyond the core domain (SEC Form D and data lookups). A more focused set of 10-15 tools would be more coherent.

Completeness4/5

The tool set covers a very broad range of data sources and actions, including SEC filings, prediction markets, entity profiling, and AI visibility. However, the completeness is uneven; for example, there are many Form D tools but few for other SEC forms, and some areas like weather or clinical trials are only accessible via ask_pipeworx.