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Glama

Connecticut 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

A4.4/5.0
Behavior5/5

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

Annotations already cover readOnly/openWorld/idempotent, so the bar is lower, and the description still adds substantial behavioral context: empty sections mean real 'no data', not a bug; private companies return resolved:false with a notes line rather than a bare failure; USPTO patents soft-fail until reactivated; fda_products may be absent for small-molecule-only companies as expected behavior; sources_used/sources_failed disclose actual coverage per company.

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?

Front-loaded with trigger phrases and the core purpose, and the length is justified by the tool's complexity (multiple data sources, edge cases, no output schema). The middle section is dense, blending source lists with return-field details and API-failure notes in a long single flow, and the trigger-phrase list is somewhat over-long, but no material information is wasted.

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 carries its weight: input formats (ticker/CIK/name), return fields (cik, company_name, recent_filings with up to 5 URIs, fundamentals from LATEST 10-K), per-source coverage reporting, and named failure behaviors (private company, no-data sections, patent API sunset). An agent knows what to expect in every notable edge case.

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 already have rich descriptions explaining interchangeable behavior and accepted input shapes. The description adds marginal value beyond the schema: the zero-padded CIK format example ('0000320193') and the resolution semantics (resolved_from/resolved_to when a name is passed). This meets the baseline 3 for high schema coverage but does not meaningfully exceed it.

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 action ('full cross-source profile of a US public company in ONE parallel call') with concrete trigger phrases ('Tell me about X', 'brief me on Tesla'). It distinguishes itself from chaining single-pack SEC/XBRL/news lookups and, by naming its cross-source scope, is clearly separable from siblings like resolve_entity, compare_entities, and deep_research.

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?

Usage context is explicit: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view', with a clear set of natural-language triggers. However, it does not route away from alternative siblings — e.g., when to use compare_entities, resolve_entity, or deep_research instead — so the when-not guidance is only partial.

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 are near-identical in purpose: ask_pipeworx and ask_pipeworx_beta are explicitly the same right now, while ai_visibility_check and scan_competitor_ai_presence overlap heavily. The only DMV-specific tool is otherwise buried among generic research, prediction-market, memory, and subscription tools that an agent would struggle to separate.

Naming Consistency3/5

Most tools use snake_case, but conventions are mixed: some are verb_noun (list_subscriptions, generate_llms_txt), some are bare verbs (remember, forget), some are brand-prefixed nouns (pipeworx_trending, polymarket_edges), and ask_pipeworx lacks a conventional verb pattern. Still readable, but not a cohesive naming scheme.

Tool Count1/5

32 tools is already heavy, but nearly all of them are unrelated to the stated Connecticut DMV scope. The server would be better served by a handful of DMV-focused tools; the current count is an extreme mismatch between name and content.

Completeness1/5

The only DMV tool is ct_dmv_ev_registrations, covering EV registration counts from a single February 2025 snapshot. There is no general vehicle registration lookup, driver licensing, plate/ VIN search, appointment, or form coverage, so the DMV domain is severely incomplete.

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