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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?

The description goes far beyond the readOnly/openWorld/idempotent annotations: it discloses the full fan-out across SEC EDGAR, XBRL, USPTO, USAspending, Purple Book, DOL LCA, news, and GLEIF; explains soft-fail behavior for the USPTO sunset; notes that empty fda_products is expected for certain companies; and clarifies that sources_used/sources_failed distinguish real no-data from bugs.

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 length is earned by the tool's complexity: it front-loads user intents, states the core behavior, then compactly enumerates return sections with semicolons. The structure is dense and scannable, though a bit of repetition around accepted value shapes could be trimmed.

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 must carry the burden of explaining return values, and it does: it enumerates cik/company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also explains edge cases like private companies, empty sections, and input resolution, so an agent has enough context to invoke it 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 coverage is 100%, so the baseline is 3, but the description adds meaningful semantics beyond the schema: it gives concrete ticker/CIK/name examples, requires zero-padded CIKs, explains name resolution via SEC EDGAR, and clarifies that type accepts 'company' or 'ticker' interchangeably. This is a clear enhancement, though the schema already covers the basic types.

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 direct user intents ('Tell me about X', 'research Acme', 'brief me on Tesla') and then states a specific, high-value purpose: a full cross-source profile of a US public company in one parallel call. It also differentiates itself from chaining single-pack SEC/XBRL/news lookups, so an agent can tell what this tool is for.

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 instructs 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving the agent a clear when-to-use rule. It also covers the private-company fallback and the expected 'no data' behavior, helping the agent choose this tool appropriately.

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 groups of tools are hard to tell apart in practice: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and bet_research all route natural-language questions to similar data sources, and the polymarket_* family plus bet_research heavily overlaps. Individual descriptions are detailed, but an agent navigating this surface will frequently struggle to choose the correct entry point.

Naming Consistency3/5

The naming is readable and mostly snake_case, but conventions are mixed: some tools are verb+noun commands (resolve_entity, validate_claim), some are noun phrases (entity_profile, bet_research), and others use product prefixes inconsistently (ask_pipeworx vs pipeworx_feedback vs polymarket_edges). The polymarket_* cluster is consistent, but no clear pattern holds across the whole server.

Tool Count2/5

34 tools is past the 25-tool threshold and is especially excessive for a server named 'translate', where only three tools relate to translation. Most of the surface belongs to a broad Pipeworx data/analytics/prediction-market platform that would be better split into separate focused servers.

Completeness3/5

The Pipeworx-related workflows are fairly well-covered: lookup, grounded research, company profiling, prediction-market analysis, subscriptions, and memory all have usable tool clusters. However, the translation domain implied by the server name is thin and references a deepl_translate tool that is not actually exposed, so there is no single domain that feels fully complete.

Resources