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Glama

Oregon 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

A4.6/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: it explains the fan-out across sources, what `sources_used`/`sources_failed` mean, that an empty section represents genuine 'no data' rather than a bug, and the resolved:false + notes behavior for private companies. The annotations already cover readonly/idempotent/nondestructive, so the description's operational detail is complementary, not redundant, and there is 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 the tool is genuinely complex and every sentence carries useful information: source behavior, failure semantics, required input formats, and edge cases. It is front-loaded with trigger examples and the core purpose before diving into details, and while it could be trimmed, the density is justified.

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?

Given there is no output schema, the description does an excellent job explaining return values: CIK and company name, resolved_from/resolved_to, recent_filings URIs, key fundamentals fields, and per-source behavior. It also covers expected failure modes (private companies, empty sections, soft-fails) and input variations, so the agent has enough context to call 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 description coverage is 100%: the schema already fully documents `type` as an enum with interchangeable values and `value` as accepting ticker, CIK, or company name. The description repeats these semantics with examples, but does not add meaningful new parameter meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 and resource: it builds a 'full cross-source profile of a US public company in ONE parallel call,' and enumerates the sources and return fields. It also distinguishes itself from chaining single-pack SEC/XBRL/news lookups, so the agent can tell it apart from sibling tools without ambiguity.

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?

The description explicitly says to prefer this tool over chaining single-pack lookups when the user asks for a holistic view, and it gives concrete trigger examples ('Tell me about X', 'research Acme'). It also explains what happens for private companies, reducing guesswork about when the tool will succeed or fail.

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 occupy the same functional space: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and the Polymarket cluster (polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, bet_research) heavily overlaps in purpose. The only clearly separated tools are the two DMV-specific ones, but they are drowned out by ambiguous data-query and prediction-market tools.

Naming Consistency4/5

Tool names mostly follow a predictable snake_case verb_noun pattern such as list_subscriptions, resolve_entity, validate_claim, and the polymarket_* / or_dmv_* prefixes are consistent. Minor deviations like bet_research, pipeworx_feedback, and ask_pipeworx_beta break the pattern slightly, but the overall style is coherent and readable.

Tool Count1/5

A server named 'Oregon DMV' exposes 33 tools, only 2 of which relate to DMV office locations and wait times. The other 31 tools form a broad general-purpose data and prediction-market platform, making the count and scope an extreme mismatch for the stated server identity.

Completeness1/5

For an Oregon DMV server, the surface is severely incomplete: there are no tools for appointments, forms, fees, licensing, registration, or services. The two DMV tools cover only office addresses and live wait times, covering a tiny slice of the domain implied by the server name.

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