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Glama

Openholidays

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

A4.8/5.0
Behavior5/5

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

The description richly discloses behavior beyond the readOnly/idempotent/openWorld annotations: it explains soft-failure behavior for patents, that empty FDA sections are expected for small-molecule companies, that sources_used/sources_failed distinguish real 'no data' from bugs, and that private companies return resolved:false with a notes line. This gives the agent reliable expectations about edge cases and partial results.

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 justifiably so given the tool's complexity and lack of an output schema. It front-loads query examples and the 'ALWAYS PREFER' guidance before diving into output details. Some redundancy exists with the schema — e.g., type and value shapes are restated — but the added behavioral detail earns the length.

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 carries the full burden of explaining return shape, and it does so thoroughly: it names each data source, describes key returned fields (e.g., recent_filings, fundamentals), notes failure semantics, and covers resolution behavior for names and private companies. An agent has enough context to invoke the tool correctly and interpret results.

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%, so the baseline is 3, but the description adds meaningful semantics: type accepts 'company' or 'ticker' interchangeably, value may be a ticker, CIK, or name, and names resolve via SEC EDGAR company-name matching. This goes beyond the schema's field descriptions and helps agents construct valid calls for varied user inputs.

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 user phrasings and clearly states the tool's core function: 'full cross-source profile of a US public company in ONE parallel call.' It also enumerates the major result sections (CIK, filings, fundamentals, patents, contracts, FDA, hiring, news, LEI), making it unmistakable what the tool does and how it differs from single-source lookups.

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 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' naming the alternative pattern and the condition for choosing this tool. It also specifies exact accepted input shapes (ticker, CIK, company name) and what happens for a private company, removing invocation ambiguity.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; multiple Polymarket tools) and many serve unrelated domains, making it hard for an agent to distinguish which tool to use for a given task, especially given the server's holiday theme.

Naming Consistency3/5

Most tool names follow a lowercase_with_underscores pattern, but the prefixes vary (ask_pipeworx, pipeworx_*, polymarket_*, etc.) and some names are less descriptive (e.g., process, run, execute-like vague verbs are absent, but still the naming lacks a unified convention across the broad set.

Tool Count2/5

35 tools is excessive for a server named 'Openholidays'. The vast majority of tools (e.g., SEC filings, Polymarket, npm scanning) are unrelated to holidays, making the tool count feel bloated and unfocused.

Completeness3/5

For the holiday domain, the server includes necessary tools (list_countries, list_subdivisions, public_holidays, school_holidays) and is complete. However, the server's actual scope is far broader, and many unrelated tools are present, which dilutes the completeness for its stated purpose.

Resources