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Glama

Bookbrainz

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 goes far beyond the annotations. It discloses that the USPTO patents source will soft-fail due to a May 2025 API sunset, that empty sections are real 'no data' (not bugs), and that a private company returns a structured resolved:false instead of failing. It also details the return structure for each data segment. This is exemplary transparency that no annotation alone could provide.

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 every sentence carries dense, useful information. The front-loading of example queries and the core value proposition immediately tells the agent what this tool is for. The structure uses semicolons and lists to pack many sources and behaviors into a compact block. While some redundancy exists (e.g., repeating the input types), the overall density justifies 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?

Given the tool's complexity (eight data sources, no output schema), the description is remarkably thorough. It explains each source, the exact return fields, fallback behavior (GDELT→GNews), and edge cases (no biologics, private companies, empty sections). An agent has everything needed to decide when to call it and what to expect in response, without needing to inspect any other schema.

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% (both parameters fully documented in the schema), so baseline is 3. The description adds extra clarity: it emphasizes that type and value are interchangeable, elaborates on the value variants (ticker, CIK, name), and notes that name resolution happens via SEC EDGAR company-name match. It also explains the resolved:false outcome for private companies, which enriches the semantics beyond the schema.

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 example queries and immediately states the core purpose: 'full cross-source profile of a US public company in ONE parallel call.' It names the specific sources (SEC EDGAR, XBRL, USPTO, etc.) and the key output fields. It also differentiates itself from chained single-pack lookups by explicitly instructing to prefer it for holistic views, which clearly distinguishes it from sibling search/lookup 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 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear when-to-use condition. It also explains the expected input types and the behavior for private companies (resolved:false with notes), which helps the agent avoid misusing it. While it doesn't list all sibling alternatives, the targeted guidance is specific and actionable.

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

The tool set mixes three distinct domains: BookBrainz entity access (browse, lookup, search), Pipeworx data routing (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, suggest_questions), and Polymarket betting analysis. Multiple tools have overlapping purposes, particularly the ask_pipeworx variants and the various polymarket_* tools, which an agent could easily confuse.

Naming Consistency4/5

All tool names follow a readable snake_case convention. While some are single verbs (browse, lookup, search), others use compound patterns (ask_pipeworx_grounded, polymarket_edge_tracker, pipeworx_trending), and there are a few noun-first names (entity_profile, pipeworx_feedback, recent_changes). The inconsistency is minor and does not hinder readability.

Tool Count2/5

With 34 tools, this is a large surface for a server named Bookbrainz, yet only 3 tools (browse, lookup, search) actually serve that domain. The remaining 31 tools are unrelated Pipeworx/Polymarket functionality, making the tool count inappropriate for the stated server purpose and suggesting a mislabeled or overloaded server.

Completeness2/5

The BookBrainz domain is severely incomplete: it offers read-only access (search, browse, lookup) but no create, update, or delete operations for entities. For the broader Pipeworx/Polymarket functionality, coverage is quite deep, but that is not the server's stated domain. This leaves a fundamental gap for the BookBrainz use case.

Resources