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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 indicate readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavior: fan-out sources, per-section response keys, sources_used/sources_failed semantics, soft-fail for the patent API sunset, expected empty FDA section for small-molecule-only companies, and resolved:false with notes for private companies. No contradiction.

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 nearly every sentence carries operational value, and the trigger examples plus 'ALWAYS PREFER' rule are front-loaded. It loses one point because the output section and source caveats could be tightened or bulleted without losing substance.

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 return-value disclosure and meets it: it enumerates every response section, flags possible empty sections as expected, and explains input and failure modes. An agent has enough to invoke it 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; the description adds meaning by showing accepted value shapes (ticker, zero-padded CIK, name), noting that name strings resolve through SEC EDGAR, and clarifying that type='company' and type='ticker' are interchangeable.

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 names a specific verb+resource: build a full cross-source profile of a US public company. It opens with user-intent examples and explicitly differentiates itself from chaining single-pack SEC/XBRL/news lookups, so an agent can tell when this tool is the holistic option.

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?

It explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' which is a clear when-to-use rule with an alternative class. It stops short of mapping all sibling tools (e.g., get_entity, compare_entities) to when-not-to-use conditions, so it isn't a 5.

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

A3.5/5.0
Disambiguation2/5

The tool set is extremely heterogeneous and overlapping. Multiple tools serve nearly identical purposes (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions), and entity-related tools (get_entity, get_wikidata_facts, entity_profile, compare_entities, resolve_entity) have unclear boundaries. The server is named Wikidata but only 3 of 34 tools actually relate to Wikidata, causing confusion about which tool is appropriate.

Naming Consistency2/5

Tool names mix multiple conventions: verb_noun (get_entity, search_entities, list_subscriptions), noun phrases (polymarket_edges, entity_profile, pipeworx_feedback), and inconsistent suffixes (_beta, _grounded). The verbs used are vague and not part of a coherent pattern (get, search, ask, discover, resolve, scan, validate, generate, remember, recall). The naming is readable but lacks a predictable system.

Tool Count2/5

34 tools is high for a server with a focused name like Wikidata, and nearly all tools belong to unrelated domains (Pipeworx data routing, Polymarket betting, memory management, subscriptions, AI visibility). The count appears bloated and scattered rather than well-scoped; most tools could be split into separate servers.

Completeness2/5

For a Wikidata server, the coverage is minimal: only search, get by ID, and human-readable facts are present, with no SPARQL query support or property-level access. The majority of tools address Pipeworx's broad data catalog, leaving the advertised Wikidata purpose severely under-served. The surface is complete for a different domain but incomplete for the stated one.