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Permid

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

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, and the description goes far beyond them: it details the fan-out across SEC EDGAR, XBRL, USPTO, USAspending, FDA Purple Book, DOL LCA, news, and GLEIF. It discloses the USPTO PatentsView API sunset soft-fail, clarifies that empty sections are real 'no data' rather than bugs, and specifies the resolved:false private-company behavior. No contradiction with annotations exists.

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 front-loaded with useful examples and high-signal detail, but it is a long, semicolon-heavy paragraph that is hard to scan. Some statements restate what the input schema already says, such as the accepted value shapes and type interchangeability, so not every word earns its place. Better bullet structure would improve readability without losing information.

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?

Because there is no output schema, the description must explain return semantics, and it does so thoroughly: it enumerates cik, company_name, recent_filings with URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also covers edge cases like empty sections, private companies, and sunsetting APIs, leaving little ambiguity for an agent deciding whether and how to call this tool.

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 value by providing concrete examples (AAPL, 0000320193, Moderna), reiterating that names resolve via SEC EDGAR's company-name match, and clarifying that type='company' and type='ticker' behave identically. This is helpful but somewhat overlaps with the schema descriptions rather than introducing fundamentally new semantics.

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 ('Tell me about X', 'research Acme', 'brief me on Tesla') and then states the core function: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from narrower or chained SEC/XBRL/news lookups, making the tool's scope and resource 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?

It gives explicit when-to-use guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also documents acceptable input shapes and the private-company resolved:false behavior. However, it does not name sibling alternatives like compare_entities or get_entity or spell out when-not-to-use conditions, so the routing guidance is strong but not exhaustive.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the set includes three very similar `ask_pipeworx` variants that could cause confusion despite detailed descriptions. The Polymarket and memory tools are well-differentiated.

Naming Consistency3/5

Names follow a mix of patterns: some `verb_noun` (ask_pipeworx, compare_entities), some `noun_noun` (entity_profile, polymarket_arbitrage), and some standalone nouns (forget, recall). While readable, the inconsistency is notable.

Tool Count3/5

At 33 tools, the server is on the heavy side for typical MCP servers (3-15 ideal). However, the broad scope covering many data domains partially justifies the count.

Completeness4/5

The tool set covers a wide range of data access and analysis needs, including entity resolution, company profiles, betting analysis, subscriptions, and memory. Minor gaps exist (e.g., no direct tool for editing entities), but overall it's well-rounded.

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