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Data Sonoma

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 readOnly/idempotent annotations, the description discloses major behavioral details: parallel fan-out across sources, the exact return sections, sources_used/sources_failed semantics, empty-section meaning real no-data, and private-company fallback behavior with resolved:false and a notes line. This gives the agent non-obvious expectations before invoking the tool.

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 examples. Each sentence adds behavioral or routing value; the main minor inefficiency is some redundancy with the schema's parameter descriptions and the unnecessary 'person/place coming soon' aside.

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 no output schema and a complex multi-source aggregation tool, the description is remarkably complete: it enumerates the return sections, source attribution, failure semantics, input normalization, and edge-case behavior. An agent has enough context to call the tool correctly and interpret results without additional lookups.

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 input schema already documents both parameters fully, so the baseline is 3. The description adds value by clarifying that type=company and type=ticker are fully interchangeable, that the same value shapes work either way, and how names resolve via SEC EDGAR, plus the private-company outcome. This is meaningful augmentation over 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 opens with concrete user queries and defines the tool as a "full cross-source profile of a US public company in ONE parallel call," making the verb, resource, and scope explicit. It also distinguishes itself from single-pack SEC/XBRL/news lookups, so an agent can recognize when this aggregator is the right choice over narrower siblings.

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 prefer this tool over chaining single-pack lookups when a user asks for a holistic view, and it gives clear accepted input forms (ticker, CIK, company name). It does not explicitly spell out when to choose sibling tools like resolve_entity or compare_entities, but the context is clear enough for most routing decisions.

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

Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded reuses the same router, and deep_research overlaps with ask_pipeworx for multi-part questions. Similarly, bet_research, polymarket_edges, polymarket_arbitrage, entity_profile, compare_entities, recent_changes, and resolve_entity all cluster around overlapping research/comparison tasks despite detailed descriptions.

Naming Consistency3/5

Names are consistently lowercase snake_case, but the naming pattern is mixed: some are verb_noun (ask_pipeworx, validate_claim, resolve_entity), some are bare nouns (datasets, metadata, polymarket_edges), some are imperative verbs (remember, forget, query), and some are adjective_noun (recent_alerts, recent_changes). The polymarket_* and pipeworx_* prefixes help, but the overall convention is not uniform.

Tool Count2/5

With 34 tools, the server exceeds the 25+ threshold and feels overstuffed for a coherent single-purpose MCP server. It spans unrelated domains: Sonoma County open data, a general structured-data router, prediction-market analysis, memory, subscriptions, npm dependency checking, and llms.txt generation—each could reasonably be its own smaller server.

Completeness4/5

The core research workflow is well covered: routing, grounded verification, entity resolution, entity profiles, comparisons, recent changes, claim validation, memory, subscriptions, and prediction-market execution checks are all present. Minor gaps exist, such as no subscription update/edit, no general pipeworx:// record-reader tool, and a read-only open-data surface, but agents can usually work around these.

Resources