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Glama

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?

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses important behaviors: empty sections are real 'no data', not bugs; private companies return resolved:false with an explicit notes line; FDA product output is expectedly empty for small-molecule/generic drugs; and there is a GDELT-to-GNews fallback. These nuances significantly help an agent interpret results correctly.

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 front-loaded with intent examples and the core directive. Most sentences add useful behavioral or output information, but some content repeats the schema (e.g., accepted value shapes) and the list of output fields is dense. Padding is minimal but not zero.

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 the return shape, and it does: cik, resolved flags, filings with URIs, fundamentals, patents, contracts, FDA products, hiring, news, LEI, and sources_used/failed. It also covers input resolution, private-company behavior, and expected empty results. Nothing an agent needs to call and interpret the tool is missing.

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 schema already covers both parameters fully, so the baseline is 3. The description adds behavioral meaning by clarifying that type values are interchangeable, names resolve via SEC EDGAR, and private companies yield a resolved:false result rather than a failure. This goes beyond the schema, but much of the value/type language duplicates what the schema already states.

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 user-intent examples and immediately states the core function: 'full cross-source profile of a US public company in ONE parallel call.' It names the specific resources covered (SEC EDGAR, XBRL, patents, etc.) and distinguishes itself from chaining single-pack lookups, making the tool's scope unmistakable.

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 says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' providing clear when-to-use guidance. It does not name specific sibling tools or state when to use an alternative, so it falls just short of full exclusion guidance.

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 heavily overlapping purposes, notably ask_pipeworx vs ask_pipeworx_beta vs ask_pipeworx_grounded, and the cluster of polymarket tools covers adjacent prediction-market analysis territory. The PomBase-specific tools are distinct, but the overall set creates real selection ambiguity.

Naming Consistency3/5

Most names follow a readable snake_case style and many use verb-first patterns, but there is notable mixing: ask_pipeworx is a brand-style exception, entity_profile and polymarket_arbitrage are noun-first, and remember/recall/forget form an inconsistent trio. Not chaotic, but not a clean predictable convention.

Tool Count2/5

33 tools is excessive for a server named Pombase, where only get_gene and get_reference actually serve that domain. Even as a broad data-research server, the count is above the 25-tool threshold and includes many auxiliary utilities that feel bolted on rather than part of a focused surface.

Completeness2/5

The PomBase-specific coverage is severely thin: only systematic-ID gene lookup and PubMed-ID reference lookup, with no gene-name search, annotations browsing, phenotype data, or sequence access. The broader Pipeworx surface is extensive, but for the apparent Pombase purpose, agents will frequently hit dead ends.