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Glama

Vessel Tracking

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 annotations already establish read-only, idempotent behavior, and the description adds substantial context: it fans out across many sources, soft-fails per source, reports sources_used and sources_failed, and clarifies that an empty section is real missing data rather than a bug. It even explains expected absences like FDA products for small-molecule companies. This is excellent 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 long but information-dense, and the most important usage guidance and examples are front-loaded. The source list and edge-case semantics are necessary for a tool this complex. Better formatting with separators would help, but there is no 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?

Given the tool's high complexity, ten data sources, and lack of an output schema, the description is unusually complete. It enumerates the returned sections (cik, filings, fundamentals, patents, contracts, fda products, hiring, news, LEI), explains failure signaling, and preempts common misinterpreations. An agent has enough context to decide when and how to invoke it 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?

The schema already documents both parameters fully, including the interchangeability of type and the accepted value shapes (ticker, zero-padded CIK, company name). The description reuses the same examples and adds resolved_from/resolved_to as output detail rather than new parameter meaning. With 100% schema coverage, the description adds little parameter-level value beyond what the schema already provides.

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 operation: a “full cross-source profile of a US public company in ONE parallel call.” It provides clear trigger examples (“Tell me about X”, “research Acme”, “brief me on Tesla”) and distinguishes itself from chained single-source lookups, making its purpose immediately recognizable.

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 to prefer this tool over chaining single-pack SEC/XBRL/news lookups when a user asks for a holistic view. It also communicates boundaries: names resolve via SEC EDGAR, private companies return resolved:false with a note, and person/place input is coming soon. This is strong when-to-use 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

A3.7/5.0
Disambiguation2/5

Several tools have significantly overlapping purposes, especially the ask_pipeworx family, deep_research, and validate_claim, plus a dense cluster of polymarket_* tools and two AI-visibility checkers. The ship-related tools are distinct, but an agent would struggle to choose among the many broadly similar query/research tools.

Naming Consistency3/5

Names are mostly snake_case and readable, but they follow no consistent convention: generic one-word verbs like remember and forget sit alongside branded names like ask_pipeworx, noun-style names like entity_profile, and prefix families like polymarket_*. The inconsistency is noticeable but not chaotic.

Tool Count2/5

34 tools is well above the well-scoped range, and the vast majority are unrelated to the server name 'Vessel Tracking'. The live-ship tools are a tiny minority buried inside a broad general-purpose data, research, and prediction-market platform, making the overall set feel bloated and misaligned with its stated identity.

Completeness1/5

As a vessel-tracking server, the surface is severely incomplete: only ais_coverage_check, live_ship_position, and live_ships_in_area relate to shipping, with no vessel lookup by name/IMO, no historical positions, no voyage data, and no port-call information. The actual tool set is rich as a general data platform, but that is not what the server name promises.

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