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Glama

Rawg

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

A4.5/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, and idempotent behavior, and the description adds substantial context: parallel fanout across sources, sources_used/sources_failed semantics, empty sections meaning genuine 'no data,' expected empty fda_products for small-molecule-only companies, GDELT→GNews fallback, and private companies returning resolved:false with a notes line. This goes well beyond the structured annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense and front-loaded with examples and the core purpose, but it quickly becomes a sprawling, semicolon-heavy paragraph. Breaking the return categories and source behaviors into a structured list would substantially improve scannability. Every entry has value, but the structural delivery hurts readability.

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?

For a complex multi-source tool with only two parameters and no output schema, the description is remarkably complete. It covers accepted input forms, resolution edge cases, expected empty results, per-source data categories, fallback behavior, and even URIs for filings. An agent has enough context to invoke the tool correctly and interpret non-standard 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?

The input schema already covers the two parameters at 100% and documents ticker/CIK/name formats. The description adds extra semantic value by explaining name resolution via SEC EDGAR, the 'resolved_from/resolved_to' behavior when a name is passed, and how private companies are handled. It goes above the schema baseline without being redundant.

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 immediately identifies the tool as a 'full cross-source profile of a US public company in ONE parallel call.' It names the resources fanned out across and the types of returned data, clearly distinguishing it from chained single-pack lookups. The verb-resource pair is specific and unambiguous.

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?

The description explicitly instructs 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 does not explicitly exclude sibling tools like compare_entities or deep_research, but it provides enough context for an agent to route holistic company-profile requests here.

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 tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx, bet_research overlaps heavily with polymarket_edges, and entity_profile/recent_changes/compare_entities/validate_claim all pull from the same SEC/news fundamentals space. The memory trio and game lookup tools are distinct, but too many other tools could be confused for one another.

Naming Consistency3/5

The surface is uniformly snake_case and has some strong families (list_*, polymarket_*, ask_pipeworx_*), but it mixes verb-led names (search_games, remember, validate_claim) with noun-led names (entity_profile, polymarket_arbitrage, pipeworx_trending) and brand-style names like ask_pipeworx. There is a pattern, but it is not a single consistent one.

Tool Count2/5

35 tools is a heavy surface, and the set feels sprawling rather than focused: a four-tool RAWG game submodule sits alongside a general-purpose research platform, Polymarket edge tooling, memory helpers, subscriptions, feedback, and meta-utilities. Many of these could have been consolidated or split into separate servers.

Completeness3/5

As a general data-research and prediction-market platform the coverage is strong, with lookup, grounded verification, entity resolution, research fan-out, and subscription flows. But for a server named Rawg, the game domain is thinly covered with only search/get/list tools and no game-detail enrichment or broader browsing surface, leaving the core domain feeling like an afterthought.

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