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Rba

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.

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the read-only and idempotent annotations, the description discloses rich behavioral details: parallel fan-out across SEC EDGAR, XBRL, USPTO, news, and GLEIF; patent API sunset with soft-fail; GDELT→GNews fallback; sorting of fundamentals by period_end; and a 'ONE parallel call' performance trait. This adds substantial context not present in the annotations.

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 front-loaded with example queries and a clear purpose statement. It packs substantial detail into a single paragraph, but the structure is monologic and could benefit from bullets for readability. However, every sentence provides useful information, so it remains efficient for a complex tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description takes responsibility for explaining return values, and it does so by listing the six output categories (cik/company_name, recent_filings, fundamentals, patents, news, LEI) with relevant limits and sorting. It also notes failure modes (patent soft-fail, news fallback). Minor gaps like exact output shape or error handling prevent a 5, but it is largely complete.

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 covers both parameters with descriptions, including the 'only company supported' note, ticker/CIK format, and the 'names not supported' caveat. The description reiterates these examples but adds no new semantic information beyond what the schema provides, so the baseline 3 for high schema coverage applies.

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 example queries and clearly states it produces a 'full cross-source profile of a US public company in ONE parallel call.' It enumerates specific sources and output fields, and distinguishes itself from single-pack lookups and sibling tools like resolve_entity. This is a specific verb+resource+scope definition.

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?

The description explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' providing a clear when-to-use directive. It also states that names are not supported and instructs to use resolve_entity first, offering a concrete alternative for the unsupported case.

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 tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language questions to the same underlying catalog, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread all target prediction-market opportunities. entity_profile, recent_changes, and compare_entities also share company-research territory, making misselection likely without reading long descriptions carefully.

Naming Consistency3/5

All names use snake_case, but conventions are mixed: some are verb_noun (list_subscriptions, generate_llms_txt, resolve_entity), some are noun phrases (entity_profile, rba_cash_rate), and some are brand-prefixed product names (ask_pipeworx, pipeworx_trending). The polymarket_* and rba_* families are internally consistent, but the overall surface has no single predictable pattern.

Tool Count2/5

35 tools is a large surface, well above the 25+ threshold that typically becomes unwieldy. While the server covers a broad domain (data lookup, prediction markets, memory, subscriptions, company research), many tools are niche variants (ask_pipeworx_beta, polymarket_edge_tracker, scan_competitor_ai_presence) that add cognitive load rather than earning their place.

Completeness3/5

Core flows are well covered: memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and data access has ask_pipeworx plus grounded and research variants. However, the surface is sprawly and uneven — prediction markets get six tools while other domain areas rely on generic routing, and the server's overall purpose is diffuse enough that gaps are hard to assess cleanly.

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