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Glama

Texas DMV

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. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already carry readOnlyHint/openWorldHint/idempotentHint/destructiveHint, and the description adds substantial behavior beyond that: the fan-out across eight named sources, USPTO PatentsView soft-fail semantics, the GDELT→GNews fallback chain, empty-section-means-real-no-data, and private-company resolved:false 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.

Conciseness3/5

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

The description is front-loaded with query examples and every clause carries substantive information, but it is a single dense run-on paragraph of semicolon-separated items with no bullets or breaks. It is wordy for an agent to parse, though none of the content is filler.

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 must explain return structure — and it does, enumerating cik, resolved_from/resolved_to, recent_filings with URIs, fundamentals fields, and each source section. It also covers failure semantics (sources_failed, soft-fails, empty as real no-data) and edge cases (private companies, name vs ticker vs CIK input). For a tool this complex, nothing essential is missing.

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% — both `type` and `value` are fully described, including the ticker/CIK/name forms and the SEC EDGAR name-resolution note. The description reinforces that 'company' and 'ticker' are interchangeable, but this duplicates what the schema enum description already states. The schema does the heavy lifting; the description adds no new parameter syntax or format details.

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 concrete user intents ('Tell me about X', 'research Acme', 'brief me on Tesla') and states a specific scope: 'full cross-source profile of a US public company in ONE parallel call.' It differentiates from siblings by declaring 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups,' which distinguishes it from single-purpose lookup tools.

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?

The description gives explicit trigger conditions (holistic-view requests about a company) and an explicit routing rule ('ALWAYS PREFER over chaining single-pack... lookups'). It also covers a key exclusion case: a private company returns resolved:false with a notes line rather than a profile. However, it never names nearby siblings like compare_entities or resolve_entity to say when to choose them instead.

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

Several tools occupy nearly interchangeable roles: ask_pipeworx and ask_pipeworx_beta are explicitly identical, while ask_pipeworx_grounded, deep_research, and validate_claim all route similar factual queries. discover_tools/suggest_questions and bet_research/polymarket_edges similarly overlap, so an agent needs to read long descriptions to avoid misselection.

Naming Consistency3/5

All names are readable lowercase snake_case, but the conventions are mixed: imperative verb_noun names (list_subscriptions, validate_claim) sit alongside noun phrases (polymarket_edges, recent_alerts), bare verbs (forget, subscribe), and variant suffixes (ask_pipeworx_beta/grounded). It is not chaotic, but there is no single predictable naming pattern.

Tool Count2/5

Thirty-two tools is far more than the apparent Texas DMV scope supports: only tx_dmv_vehicle_registrations is DMV-related, and the rest are Pipeworx platform, prediction-market, memory, and unrelated utility tools. The count is excessive for the server's stated name and purpose.

Completeness1/5

The Texas DMV surface is severely incomplete: a single statewide registration-count tool covering fiscal years 2001-2021, with no title/registration transactions, VIN lookup, driver services, county/ZIP breakdowns, or current data. The tool's own description references a California DMV companion that is not present, leaving obvious gaps for any realistic DMV workflow.

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