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Glama

timezone

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

A4.6/5.0
Behavior5/5

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

The annotations only cover readOnly/openWorld/idempotent/non-destructive safety, so the description carries the behavioral load. It discloses the source fan-out, the return contract, the 'empty section is a real no data' semantics, the patents API sunset soft-fail, and the resolved:false behavior for private companies. There is no contradiction with the readOnlyHint.

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 front-loaded with trigger phrases and organized by source, and nearly every sentence earns its place given the tool's complexity. However, the opening string of six near-synonymous examples and the repetition of `type` interchangeability in both description and schema keep it from being maximally concise.

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 fully specifies the return structure (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed). It also covers input shapes, failure modes, and expected empty results, so an agent has enough context to select and invoke the tool correctly.

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%, giving the baseline of 3. The description then adds value by clarifying that `type` accepts either enum value interchangeably, that `value` can be a ticker, zero-padded CIK, or company name, and that names resolve via SEC EDGAR's company-name match. This goes beyond the schema but is not drastically new information.

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 opens with concrete natural-language triggers and defines the tool as a 'full cross-source profile of a US public company in ONE parallel call.' It names the exact resource (company profile) and verb/scope, and contrasts it with chaining single-pack SEC/XBRL/news lookups, so it is distinguishable from siblings like deep_research or resolve_entity.

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?

It explicitly says to prefer this tool when the user asks for a holistic view ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'), and it explains edge-case behavior for private companies and name resolution. It does not enumerate explicit when-not-to-use conditions or name sibling tools, so it stops short of a 5.

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

Many tools have overlapping purposes, especially the multiple 'ask_pipeworx' variants and several Polymarket utilities. The server mixes a few timezone tools with a large collection of unrelated data lookup and analysis tools, making it hard for an agent to distinguish which tool to use for a given task.

Naming Consistency2/5

While all tool names use snake_case, the verbs are highly inconsistent (e.g., 'ask_pipeworx', 'convert_time', 'discover_tools', 'validate_claim'). There is no clear pattern or predictable naming convention across the set.

Tool Count2/5

The server name 'timezone' suggests a narrow domain, but it contains 35 tools, the vast majority of which are unrelated to timezones. This is far too many for the implied scope, and the server seems to be a dumping ground for various services.

Completeness1/5

For a timezone server, only 4 tools (convert_time, get_time_by_ip, get_time_by_timezone, list_timezones) are relevant. Critical timezone functionality like time zone conversions with arbitrary offsets, DST handling, or time zone by coordinates is missing. The remaining tools are completely unrelated to the server's stated purpose.

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