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Glama

Gnomad

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?

Annotations already mark it read-only, idempotent, and non-destructive, so the bar for added behavioral context is high. The description exceeds it by explaining sources_used/sources_failed semantics ('an empty section is a real "no data", not a bug'), the USPTO PatentsView sunset soft-fail, expected-empty FDA sections for small-molecule-only companies, and private-company resolved:false behavior. This substantially exceeds what annotations alone convey.

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 example user intents and the core 'ALWAYS PREFER' directive, then organizes return sections with clear semicolon-separated field names. It is long and dense, but nearly every clause carries unique operational detail rather than filler, so it earns a score above minimum despite not being brief.

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 bears the burden of explaining return values, and it does: it covers every returned section (recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), source-failure semantics, input resolution behavior, and edge cases like private companies. An agent has enough to invoke and interpret 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 description coverage is 100%, so the baseline is 3. The description adds concrete value by explaining that type accepts 'company' or 'ticker' interchangeably, providing examples ('AAPL', '0000320193', 'Moderna'), and noting that names resolve via SEC EDGAR. It adds useful nuance beyond the schema, though it partially repeats it.

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 natural-language triggers and states the deliverable: 'full cross-source profile of a US public company in ONE parallel call.' It clearly identifies the verb, resource, and scope, and distinguishes itself from siblings like resolve_entity and compare_entities by its breadth and single-entity focus.

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 instructs 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear routing signal. It also defines acceptable input forms and private-company behavior, but it does not contrast this tool against deep_research or compare_entities, so not all alternatives are addressed.

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

B3.4/5.0
Disambiguation2/5

The set mixes several overlapping query surfaces: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded/deep_research/discover_tools/suggest_questions all serve related retrieval/discovery purposes, and the five polymarket_* tools have similar opportunity-finding goals. Only the unusually detailed descriptions save some tools from misselection; an agent would struggle to quickly pick the right one.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow a verb_noun or prefixed_noun pattern (ask_pipeworx, validate_claim, polymarket_edges, scan_dependency). Minor inconsistencies exist — bare nouns like gene/variant/search sit alongside compound names like generate_llms_txt, and the pipeworx_ prefix isn't applied to ask_pipeworx/deep_research — but the overall style is recognizable and predictable.

Tool Count2/5

36 tools is too many for a coherent server, especially since the domains are largely unrelated: 5 gnomAD genomics tools, 20+ Pipeworx/Polymarket data tools, memory CRUD, subscription management, and a couple of web-dev utilities. The count doesn't align with a single obvious scope and would overwhelm an agent selecting among them.

Completeness3/5

Within the major subdomains coverage is strong: memory has remember/recall/forget, subscriptions have full lifecycle tools, and Polymarket has edge detection plus fill-risk checking. However, there are notable gaps — no tool to fetch a pipeworx:// citation URI despite deep_research promising resolvable citations, and the gnomAD surface lacks batch queries, coverage, or constraint data for a server named Gnomad.

Resources