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Glama

Epss

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

A4.9/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, open-world behavior; the description adds substantial context beyond that by enumerating the fan-out sources, explaining what each returned section means, and explicitly stating that an empty section is 'a real "no data", not a bug.' It also discloses the name resolution behavior and the resolved:false fallback for private companies, which are important non-obvious traits.

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 dense but well-structured, front-loading user intents and the core preference rule before detailing sources and return fields. The heavy use of parenthetical asides makes it somewhat hard to scan, but each sentence earns its place and the length is justified by the tool's complexity.

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 tool with no output schema, the description provides a thorough overview of the response shape, source coverage, failure semantics, and input edge cases. An agent has enough context to select and invoke the tool correctly in most realistic scenarios, including handling private companies and empty sections.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Though schema coverage is 100%, the description enriches both parameters with practical examples ('AAPL', '0000320193', 'Moderna'), states that type values are interchangeable, and explains the resolved_from/resolved_to behavior for name inputs. This goes well beyond the schema's enum and basic descriptions.

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 clearly states the tool produces a 'full cross-source profile of a US public company in ONE parallel call,' with concrete user query examples. It also explicitly distinguishes itself from 'chaining single-pack SEC/XBRL/news lookups,' making its purpose unambiguous relative to siblings.

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?

It gives explicit guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also specifies acceptable input types, clarifies that private companies return resolved:false, and notes that 'person/place coming soon,' setting clear boundaries for when the tool applies.

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

A3.7/5.0
Disambiguation2/5

Several tools occupy overlapping functional space: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and bet_research, polymarket_edges, and polymarket_arbitrage all target Polymarket opportunity detection. The detailed descriptions help, but an agent can easily select the wrong query/research or prediction-market tool.

Naming Consistency3/5

Most names are readable snake_case and clusters like polymarket_* and pipeworx_* are internally consistent. However, the overall set mixes verb_object names (compare_entities, resolve_entity), bare verbs (forget, subscribe), and noun phrases (entity_profile, recent_alerts, top_exploited), so there is no unifying naming convention.

Tool Count2/5

At 33 tools, the count exceeds the reasonable threshold for a focused server, and the problem is worse because the server is named Epss while most tools are Pipeworx data, Polymarket, memory, and subscription tools. A focused EPSS server would need only a handful of tools; this is a grab bag.

Completeness2/5

For the EPSS purpose implied by the server name, only get_epss and top_exploited exist, with no CVE search, historical score context, or vulnerability-management tooling. The unrelated research, memory, and prediction-market tools are individually fairly complete, but they do not fill the gap for the apparent EPSS use case.

Resources