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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?

Beyond the readOnlyHint, openWorldHint, and idempotentHint annotations, the description adds rich behavioral context: it lists the fan-out sources, notes the USPTO patents soft-fail, explains that empty sections are 'a real no data, not a bug', describes the fallback chain (GDELT→GNews), and covers the resolved:false case for private companies. This goes well beyond the annotation hints and is consistent with them.

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 information-dense. It front-loads example phrasings and the core purpose, then enumerates sources, return fields, parameter nuances, and edge cases. Every sentence adds value; the only reason it is not a 5 is that it is quite verbose, though the complexity of the tool justifies it. There is no wasted fluff.

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?

Since there is no output schema, the description must fully explain return values and edge cases. It does so comprehensively: it lists all return sections (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), explains that empty sections are normal, and covers private company handling. It leaves nothing ambiguous for an agent needing to call the tool correctly.

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 description coverage is 100% (both type and value are described). The description adds nuance: it states the two type values are interchangeable, clarifies that value can be a ticker, zero-padded CIK, or company name, and mentions SEC EDGAR name resolution. This is more than just repeating the schema, so it earns a point above the baseline of 3.

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 clearly states the tool's purpose: 'full cross-source profile of a US public company in ONE parallel call' with example phrasings like 'Tell me about X'. It explicitly differentiates from chaining single-pack lookups by stating 'ALWAYS PREFER over chaining...' and lists the sources involved, making the tool's scope unmistakable and distinct 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 Guidelines4/5

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

The description gives explicit guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view' and provides trigger examples. It does not explicitly say when NOT to use this tool (e.g., for non-company research), but the intended use case is well-scoped and the guidance is strong enough for an agent to decide.

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

B3.1/5.0
Disambiguation2/5

Several tools occupy overlapping boundaries: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicate query entry points (beta is currently identical), while ladder/standings, ai_visibility_check/scan_competitor_ai_presence, and polymarket_edges/polymarket_arbitrage also blur together. An agent would struggle to reliably pick the right tool without reading very long descriptions.

Naming Consistency4/5

The vast majority of names are snake_case and many follow a readable verb_noun shape, such as resolve_entity, validate_claim, and list_subscriptions. However, the Squiggle/AFL tools are bare nouns (games, ladder, sources, standings, teams, tips), and the polymarket_* / pipeworx_* prefixes do not use one consistent verb style, so it is not a fully uniform convention.

Tool Count2/5

37 tools is in the too-many band, and the sprawl is compounded by mixing unrelated domains under one server: AFL stats, a huge Pipeworx data-routing layer, prediction-market analytics, AI visibility checks, npm dependency review, and llms.txt generation. The set feels like several merged servers rather than one well-scoped MCP.

Completeness3/5

The query/research surface is broad and covers many subdomains, and the subscription lifecycle is reasonably complete with subscribe/list/unsubscribe/recent_alerts. However, pipeworx:// citation URIs are prominently returned but no tool fetches a cited record directly, the AFL side lacks player-level data, and subscriptions cannot be updated.