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Glama

Fda Devices

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

A4.6/5.0
Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses many behavioral traits: it fans out across multiple sources, returns sources_used/sources_failed, treats empty sections as real no-data rather than bugs, soft-fails for USPTO patents, and handles private companies with a resolved:false plus notes. This is rich, action-relevant context.

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 and long, but every section adds operational value: trigger phrases, source list, return shape, failure semantics, and input forms. It is front-loaded with the core purpose and examples, and the detailed source/failure explanation is justified given 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?

With no output schema, the description carries the full burden of explaining return values, and it does so thoroughly: cik, company_name, recent_filings with URIs, fundamentals fields, per-source sections, sources_used/sources_failed, and resolved:false behavior for private companies. It also covers input normalization and expected empty results.

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

Parameters3/5

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

The input schema already documents the parameter meanings thoroughly, including accepted forms for value and interchangeability of type, so schema coverage is 100%. The description mostly restates and occasionally expands on that, such as noting private-company resolution behavior, but it does not add substantial new parameter semantics 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 states a specific verb and resource: it produces a full cross-source profile of a US public company. It clearly distinguishes itself from single-pack SEC/XBRL/news lookups and from related profile tools by emphasizing the parallel, holistic nature of the call.

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 trigger examples ('Tell me about X', 'research Acme', 'brief me on Tesla') and explicitly says to prefer it over chaining single-pack lookups when a holistic view is requested. It also clarifies how to handle private companies — they will return resolved:false rather than succeeding, which is a de facto usage boundary.

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

A3.5/5.0
Disambiguation2/5

The FDA-specific tools are distinct, but they are mixed with many generic Pipeworx tools (e.g., ask_pipeworx variants, deep_research, entity_profile) that have overlapping purposes. This creates significant ambiguity for an agent trying to choose the right tool for FDA-related queries.

Naming Consistency2/5

Tool names follow two inconsistent patterns: FDA tools use 'fda_device_*' (consistent), while generic tools use various patterns like 'ask_pipeworx', 'deep_research', 'remember', etc. The mix of snake_case, camelCase, and descriptive phrases lacks coherence.

Tool Count2/5

With 37 tools, the count is high for what is intended as an FDA devices server. Only 6 tools are directly FDA-related; the rest are generic and dilute the purpose. The scope is mismatched, making the tool count inappropriate.

Completeness3/5

The FDA tools cover key areas: 510k search, adverse events, PMA, recalls, company profiles. However, the server is incomplete for its name because it lacks many tools that a comprehensive FDA devices server would have, and the generic tools don't fill those gaps.

Resources