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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?

Even though annotations already mark this as read-only and idempotent, the description adds substantial operational transparency: it fans out in parallel, soft-fails on the USPTO sunset, treats empty FDA sections as expected rather than errors, uses sources_used/sources_failed to distinguish real no-data from bugs, and explains name resolution and private-company behavior. No contradiction with 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 front-loaded with strong query triggers and is dense with useful detail, but it is a long single block that mixes examples, source enumeration, return fields, and edge cases. Each sentence earns its place, but formatting/bulleting would improve scannability.

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?

For a complex tool with no output schema, the description is remarkably complete: it lists every major return section, explains sources_failed/sources_used, pre-empts false negatives, describes input forms, and covers the private-company resolution flow. An agent has what it needs to invoke 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.

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, but the description adds meaningful clarification: both 'company' and 'ticker' values behave identically, 'value' accepts ticker, zero-padded CIK, or company name, and names resolve through SEC EDGAR. This reinforces the schema and removes ambiguity about interchangeability.

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 queries and states the core operation: building a 'full cross-source profile of a US public company in ONE parallel call.' It enumerates the fan-out sources and return fields, making it unmistakably distinct from generic profile tools and from chained single-source 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?

Explicit trigger phrases are provided ('Tell me about X', 'research Acme', 'brief me on Tesla'), and the description instructs the agent to 'ALWAYS PREFER' this tool over chaining SEC/XBRL/news lookups when a holistic view is requested. It also clarifies edge cases like private companies returning resolved:false, which tells the agent when a different tool or path is needed.

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

ask_pipeworx and ask_pipeworx_beta are currently described as functionally identical, creating a clear misselection risk, and several query/answer tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, compare_entities) have overlapping boundaries. The Polymarket tools also blur into each other, so despite verbose descriptions, an agent can easily route a request to the wrong tool.

Naming Consistency3/5

All names are snake_case and readable, but the conventions are mixed: verb_noun (ask_pipeworx, resolve_entity), noun_noun (entity_profile, bet_research), bare verbs (remember, recall, forget, profile), and prefix families with inconsistent ordering (ask_pipeworx vs pipeworx_feedback, polymarket_edges vs polymarket_kalshi_spread). This is not chaotic, but there is no single predictable naming pattern.

Tool Count2/5

36 tools is well past the 25+ threshold for a heavy surface, and the server name 'Mojang' implies a narrow Minecraft API scope while only 5 tools relate to Minecraft. The rest belong to a broad data-research, prediction-market, and memory platform, making the tool count feel inflated and mis-scoped for the server's stated identity.

Completeness2/5

For the implied Minecraft/Mojang domain, there are obvious gaps such as no authentication, skin/name mutation, or broader account endpoints, so that surface is thin. Meanwhile, the Pipeworx data side is fairly complete, but because two unrelated domains are jammed into one server, neither domain is covered in a coherent, trustworthy way.