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Glama

gutendex

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

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent, but the description adds substantial operational detail: it fans out across multiple sources in parallel, soft-fails when the USPTO patents API is sunset, treats missing FDA products as expected rather than an error, and explains that empty sections in sources_used/sources_failed are real 'no data'. This goes well beyond the annotations.

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 complex and there is no output schema, so most sentences earn their place by clarifying sources, return fields, or failure semantics. It is front-loaded with examples and the core profile promise. Some restructuring could improve scannability, but there is little waste.

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 breadth and the absence of an output schema, the description carries the full burden and succeeds. It enumerates every returned section, explains which sources contribute to each, details edge cases like private companies and expected empty FDA results, and names fallback behavior for news. An agent has enough context to invoke it correctly without further inference.

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 description coverage is 100%, so the schema already documents type and value. The description adds extra meaning by stating that 'company' and 'ticker' are interchangeable, that value can be a ticker, zero-padded CIK, or name, and that names resolve through SEC EDGAR. This is useful complement rather than needless repetition.

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 produces a full cross-source profile of a US public company in one parallel call. Query examples ('Tell me about X', 'research Acme', 'brief me on Tesla') make the intended use unmistakable. It also distinguishes itself from chained single-source lookups, which helps an agent pick it over more granular tools.

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 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving clear when-to-use guidance. It also specifies acceptable input forms (ticker, CIK, name) and expected behavior for private companies, so an agent can route calls correctly.

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

Multiple tool clusters are nearly indistinguishable: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded overlap heavily (beta is explicitly identical right now), and five polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all concern prediction-market edge detection with fuzzy boundaries. entity_profile, recent_changes, and compare_entities also blur together for company research. Only the book tools are cleanly distinct, but they are drowned by the surrounding ambiguity.

Naming Consistency4/5

Most tools follow a consistent snake_case pattern and generally lead with a verb or clear noun (search_books, get_book, subscribe, unsubscribe, validate_claim, resolve_entity). A few depart from the verb-first convention (entity_profile, bet_research, pipeworx_trending, polymarket_edges) but the deviations are minor and do not hinder readability.

Tool Count2/5

35 tools is already heavy, but the critical problem is scope: the server is named gutendex (a book API) yet only 4 of 35 tools relate to books, with the other 31 forming an unrelated Pipeworx data/research/prediction-market suite. The count is inappropriate for the advertised purpose — it feels like two or three separate servers crammed into one.

Completeness2/5

For the gutendex domain, the book tools are thin: search, get, popular, and topic browsing exist, but common Gutendex capabilities like author browsing, language filtering, sorting, and pagination controls are missing. For the actual Pipeworx suite the surface is broad, but the server's stated purpose is gutendex, and the overwhelming majority of tools are completely off-topic, creating a severe coverage mismatch.

Resources