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Glama

trivia

by io.github.pipeworx-io

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. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive, and the description goes far beyond these by disclosing fan-out sources, soft-fail behavior for USPTO, the expected-empty semantics for FDA products, sources_used/sources_failed, and the resolved:false behavior for private companies. This is exemplary behavioral disclosure.

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 dense and front-loaded with query examples and the always-prefer directive. It is long, but the length is justified by the number of sources and edge cases; however, the single run-on paragraph structure could be improved with lists or separate breaks for 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?

There is no output schema, so the description fully carries the burden of explaining return values. It enumerates cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used, and sources_failed, including semantics for empty sections. The tool is complex, and the description covers all important calling and interpretation scenarios.

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 genuine semantic value by explaining that 'type' accepts company/ticker interchangeably, that value can be a ticker/CIK/name, and that names resolve via SEC EDGAR, including resolved_from/resolved_to behavior beyond the schema's parameter descriptions.

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 states a specific verb-resource pair: it provides a 'full cross-source profile of a US public company in ONE parallel call.' It distinguishes itself from chaining single-pack lookups and from generic research or entity-resolution tools, so an agent can select it confidently.

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?

It explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies accepted inputs (ticker, CIK, company name) and the expected behavior for unsupported private companies, giving clear when-to-use and edge-case guidance.

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

A3.6/5.0
Disambiguation2/5

Several tools have notably unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and polymarket_edges, polymarket_arbitrage, and bet_research heavily overlap in surfacing betting opportunities. Entity_profile, recent_changes, and compare_entities also share overlapping research scope, making misselection likely.

Naming Consistency3/5

Most names use snake_case and a roughly readable verb_noun style (resolve_entity, compare_entities, list_categories), but conventions vary: some are bare nouns (entity_profile), some are plain verbs (remember, forget), and ask_pipeworx/pipeworx_* break the pattern. It is readable overall, but not a consistent scheme.

Tool Count2/5

34 tools is far more than the 'trivia' name implies, and most of them (Pipeworx research, Polymarket analysis, memory, subscriptions) are unrelated to trivia. The set reads as an entire platform bundled together rather than a purpose-scoped server.

Completeness2/5

For the stated trivia purpose, the surface is missing core lifecycle features like quiz sessions, answer validation, or scoring; the few trivia tools are just category/reference lookups. As a general data/research server it is broad, but there are significant gaps and no coherent domain model tying the tools together.

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