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Glama

Nasa

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

A4.8/5.0
Behavior5/5

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

The description discloses rich behavioral detail beyond the readOnly/idempotent annotations: USPTO PatentsView sunset soft-fails, an FDA section with no biologics is normal, sources_used/sources_failed indicate real no-data, private companies return resolved:false with notes, and names resolve via SEC EDGAR. This goes far beyond what annotations provide and prevents misinterpretation.

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 dense and front-loaded with purpose and usage before source and return details. Every sentence carries necessary behavioral or routing information; a slight restructure into shorter bullets could improve readability, but nothing here is filler.

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?

Given there is no output schema, the description fully compensates by enumerating the returned sections, interpreting empty sections, explaining fallback chains, and specifying input and resolution behavior. It even covers failure modes and API sunset conditions, making the tool safely invocable by an agent with no additional context.

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 useful semantic extras: type accepts 'company' or 'ticker' interchangeably, value can be a ticker, zero-padded CIK, or company name, and name resolution behavior is clarified. It reinforces and expands on the schema without introducing new ambiguity.

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 names a specific, differentiated action: producing a full cross-source profile of a US public company in one parallel call, with concrete user-phrase examples. It also distinguishes itself from chaining individual SEC/XBRL/news lookups, so an agent can tell it apart from narrower or broader 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 explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' which is a clear when-to-use rule. It also gives exclusions: private companies yield resolved:false with notes, and person/place is 'coming soon,' signaling this tool is scoped to companies.

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 nearly identical semantic space: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route through the same 5,798 tools and differ mainly in output strictness or testing status. The Polymarket cluster also has significant boundary overlap, and the 'Nasa' server name makes the large block of unrelated data tools even more confusing to navigate.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern (get_apod, search_nasa_images, resolve_entity, validate_claim, unsubscribe), and family prefixes like ask_pipeworx and polymarket_ are consistent. A few noun-first outliers like entity_profile, deep_research, and bet_research break the pattern slightly, but the overall style is still readable and predictable.

Tool Count2/5

With 36 tools, this set is well beyond the comfortable 3-15 range and even exceeds the 16-25 'heavy' band. Only about five tools actually relate to the server's apparent NASA identity, while the rest form a general data/Pipeworx utility kit that would be better split into a separate server.

Completeness2/5

For a server named 'Nasa,' the surface is thin: APOD, asteroids, Mars rover photos, solar flares, and image search cover only a slice of NASA's API portfolio, with no launch schedules, Earth imagery, mission/news feeds, or ISS data. The general Pipeworx tools make the server broad but incoherent, and a user focused on NASA would hit dead ends quickly.

Resources