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Glama

Eia

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

A4.6/5.0
Behavior5/5

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

Annotations already mark the tool read-only and idempotent, and the description adds substantial non-obvious behavior: it fans out across named sources, soft-fails on the USPTO sunset, treats an empty FDA section as expected rather than a bug, returns resolved:false with a notes line for private companies, and documents sources_used/sources_failed. This goes far beyond 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 long but information-dense and well front-loaded: it opens with realistic user phrasings and the core 'ONE parallel call' promise before detailing return sections. Almost every sentence adds operational value; it only slightly repeats schema enum descriptions, which keeps it from a perfect conciseness score.

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?

There is no output schema, so the description carries the full burden of explaining return behavior—and it does so thoroughly: cik/company_name, filing URIs, fundamentals, patents, contracts, FDA products with the expected-empty caveat, hiring, news fallback, LEI, and failure section semantics. An agent has enough to invoke and interpret the result 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. The description extends this by clarifying that ticker, CIK, and company name are all interchangeable, that 'company' and 'ticker' behave identically, and that name resolution goes through SEC EDGAR. It also explains the failure mode for private companies, which is genuinely useful beyond the schema.

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 anchors on explicit user intents ('Tell me about X', 'research Acme', 'brief me on Tesla') and names the core function: a full cross-source profile of a US public company in one parallel call. It also differentiates itself from single-pack lookups by emphasizing 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'.

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 an explicit trigger ('when the user asks for a holistic view') and an explicit preference rule ('ALWAYS PREFER over chaining single-pack...'). It does not explicitly name sibling alternatives like compare_entities or resolve_entity, but it clearly communicates when this tool should win over fragmented lookups and notes the person/place limitation.

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

Several tools occupy nearly identical roles: ask_pipeworx and ask_pipeworx_beta are described as currently identical, ask_pipeworx_grounded and deep_research overlap with the router, and eia_series overlaps with the specialized eia_electricity/eia_ethanol/eia_natural_gas/eia_petroleum tools. The Polymarket opportunity scanners and the two AI-visibility checkers also blur together, making confident tool selection difficult despite detailed descriptions.

Naming Consistency3/5

Most tools follow a snake_case verb-first pattern (remember, recall, forget, resolve_entity, validate_claim), but there are notable deviations: eia_electricity and eia_ethanol are noun-first category names, recent_alerts and recent_changes are adjective-noun, and pipeworx_trending and polymarket_edges are not verb-driven. The eia_ and polymarket_ prefixes add some predictability, so the naming is readable but inconsistent.

Tool Count2/5

At 36 tools, this is well past the heavy threshold and feels like a kitchen-sink aggregation of several separate products rather than one focused server. Many tools could be consolidated: the five eia_* lookups, the multiple ask_pipeworx variants, and the several Polymarket scanners all serve close purposes. A 36-tool surface is too much for an agent to navigate efficiently.

Completeness4/5

Within the major subdomains the set is quite complete: entity research has profile/compare/changes/resolve, memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and Polymarket analysis has edge discovery, fill-risk, venue-spread, and persistence tracking. Minor gaps exist—no subscription update flow, no dedicated EIA coal/nuclear/renewables series beyond the generic eia_series fallback—but agents can work around them.

Resources