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Glama

Weather

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?

Beyond the read-only/idempotent annotations, the description discloses fan-out architecture, soft-failure for USPTO patents, expected empty fda_products for non-biologic companies, and the meaning of sources_used/sources_failed. It also clarifies that empty sections are real 'no data' rather than bugs, which is essential non-obvious behavioral 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 long but front-loaded with purpose and example queries, and the dense detail that follows earns its place by explaining return fields, edge cases, and failure semantics. Some trimming is possible, but for a tool this complex the length is justified.

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 present, the description compensates by enumerating all major return fields (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed) and covering resolution behavior and expected no-data cases. An agent has enough context to invoke the tool and interpret its results 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?

The schema already documents type and value clearly, and the description goes further by stating that type='company' and 'ticker' behave identically, that value can be a ticker, CIK, or name, and that names resolve via SEC EDGAR's company-name match. It also explains private-company resolution results, adding meaning beyond the schema fields.

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 natural-language triggers and states a specific action: building a full cross-source profile of a US public company in ONE parallel call. It clearly distinguishes the tool from piecemeal SEC/XBRL/news lookups by emphasizing the holistic single-call behavior, even if sibling tool names are not explicitly listed.

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?

The description explicitly says to use this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view, giving a clear selection condition. It also explains private-company behavior, but it does not name alternative sibling tools like resolve_entity or compare_entities or state when those should be preferred.

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 have overlapping purposes, particularly the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) where the beta variant is currently identical to the stable one, creating selection ambiguity. Additionally, many data-lookup tools (entity_profile, compare_entities, recent_changes, validate_claim) could be confused for similar queries, and the three weather tools are buried among unrelated prediction-market and utility tools.

Naming Consistency2/5

Tool names are all snake_case, but the pattern is inconsistent: some are verb-first (get_forecast, list_subscriptions, remember), while others are noun-first or noun phrases (polymarket_edges, pipeworx_trending, entity_profile, bet_research). The mix of verbs and nouns without a clear convention makes the interface feel unstructured.

Tool Count1/5

With 34 tools, the count is far too high for a server nominally focused on weather, which only has 3 relevant tools. The majority of tools are unrelated to weather (Pipeworx data, prediction markets, memory, subscriptions), making the scope seem bloated and misaligned with the server name.

Completeness3/5

For the weather domain itself, the coverage is adequate (real-time, forecast, historical), but the server includes many unrelated tools that create confusion about its true purpose. The extra tools neither enhance weather functionality nor form a coherent secondary domain, leaving the overall surface feeling incomplete for a single coherent use case.

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