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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 safe read-only behavior, and the description adds substantial behavioral detail beyond that: the exact sources fanned out, the return fields, sources_used/sources_failed semantics, GDELT→GNews fallback, and private-company resolved:false behavior. This gives the agent a strong mental model of what happens when invoked.

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, with no wasted sentences. It is front-loaded with example queries and the core purpose, then systematically enumerates sources, returns, and edge cases. Slightly run-on in places, but every clause contributes useful guidance.

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 the full burden of explaining return values, and it does so thoroughly: it lists all output sections, explains the meaning of empty sections, and documents resolution behavior for private companies. Nothing critical is missing for an agent to select and invoke the tool correctly.

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%, so the baseline is 3. The description reinforces the schema with examples ('AAPL', '0000320193', 'Moderna') and states that type values are interchangeable, but the schema already conveys this. The description adds little beyond what the parameter descriptions provide.

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 a precise statement of purpose: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from sibling tools by directing agents to prefer it over chaining single-pack SEC/XBRL/news lookups.

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 when to use: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also implies the alternative (use single-pack tools for narrow requests) and covers edge cases like private companies, making the selection criteria clear.

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

Several clusters have overlapping purposes: ask_pipeworx and ask_pipeworx_beta are explicitly identical, and the five prediction-market tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_kalshi_spread, polymarket_fill_risk) all target 'find edge in Polymarket markets' with subtle differences. query and variant both retrieve the same variant annotations, and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates.

Naming Consistency4/5

Most tools follow a consistent verb_noun or domain-prefixed pattern (ask_pipeworx, compare_entities, resolve_entity, polymarket_edges, remember/recall/forget). Minor deviations exist: the bare nouns query, variant, and metadata are less descriptive, and ask_pipeworx_beta uses a suffix instead of a clean verb pattern, but the overall convention is fairly uniform.

Tool Count2/5

34 tools is far too many for a server named 'Myvariant' whose stated domain is genetic variant annotations. The set is a grab-bag spanning genetic data, Pipeworx query routing, Polymarket betting, memory persistence, subscriptions, AI visibility, and npm dependency scanning. Most tools are unrelated to the server's apparent purpose, making the count feel bloated and incoherent.

Completeness3/5

Individual clusters are reasonably complete: variants have search/get/metadata, memory has remember/recall/forget, and subscriptions have subscribe/list/unsubscribe/alerts. However, as a Myvariant server the surface is massively over-scoped yet oddly missing any batch-variant or annotation-source-specific lookup, and the sprawling multi-domain design makes 'complete' hard to meaningfully assess.