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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

A4.5/5.0
Behavior5/5

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

Adds significant context beyond annotations: fans out across multiple external sources, explains sources_used/sources_failed semantics, clarifies empty means 'no data' rather than an error, and describes the private-company resolved:false behavior. The readOnly/openWorld/idempotent hints are reinforced rather than contradicted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with examples and core purpose, but quickly becomes a dense, sprawling paragraph with many parentheticals and repeated details. It would benefit from structured bullets or clearer sectioning; while no sentence is entirely wasted, the length and run-on style reduce readability.

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 bears full responsibility for explaining return values and edge cases. It covers all major data sections (recent_filings, fundamentals, patents, contracts, biologics, hiring, news, LEI), denotes sources_used/sources_failed, handles name resolution and private companies, and explains input flexibility—complete for a tool of this complexity.

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% and the parameter docs already include the same examples, zero-padding guidance, and the company/ticker interchangeability. The description adds only minor extras like 'person/place coming soon' and output-level resolved_from/resolved_to detail, which does not materially enhance parameter understanding.

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 user intents ('Tell me about X', 'research Acme') and a precise resource: 'full cross-source profile of a US public company in ONE parallel call.' It clearly differentiates itself from single-pack SEC/XBRL/news lookups and implies a holistic profile vs. narrower siblings like resolve_entity or search_news.

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 states 'ALWAYS PREFER over chaining single-pask SEC/XBRL/news lookups when the user asks for a holistic view', providing a clear condition and alternative. It also specifies accepted input forms (ticker, zero-padded CIK, or name) and how private companies are handled, leaving little to inference.

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

A3.7/5.0
Disambiguation2/5

Several tool clusters are hard to tell apart: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical routers (beta currently behaves exactly like stable), and the six polymarket_* tools plus bet_research all overlap around edge and arbitrage discovery. The descriptions are detailed and help, but an agent must read carefully to avoid misselecting a sibling tool.

Naming Consistency3/5

Names are consistently lowercase snake_case, but the verb/noun ordering is mixed: verb-first names (ask_pipeworx, list_categories, resolve_entity) coexist with noun-first names (polymarket_edges, entity_profile, pipeworx_feedback, recent_alerts) and bare verbs (remember, recall, forget). Readable overall, but the pattern is not systematic.

Tool Count2/5

34 tools is well beyond the 25+ threshold and spans at least six loosely related domains (news, structured data research, prediction markets, AI visibility, memory, subscriptions), making the server feel like a multi-product grab bag. Meta-tools like discover_tools, suggest_questions, and pipeworx_trending add further navigation overhead.

Completeness4/5

Within each bundled domain the lifecycle is well covered: data lookup has routing, grounded mode, deep research, entity resolution, comparison, and claim validation; Polymarket has research, arbitrage, edge, fill-risk, and cross-venue spread tools; memory and subscriptions each have full CRUD-ish flows. Minor gaps like subscription updating or direct article-by-ID fetching are workarounds rather than dead ends.