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Transport Feeds

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

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses that it fans out across multiple sources, that empty sections mean real absence of data rather than errors, that private companies return resolved:false with a notes field, and that type values are interchangeable. This significantly enhances the agent's ability to interpret results.

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 examples; every sentence adds operational detail. However, it repeats the accepted input shapes in a couple of places and could be tightened slightly without losing essential meaning.

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 details both the fan-out sources and the returned sections (cik, company_name, recent_filings, fundamentals, sources_used/failed), explains expected edge cases, and clarifies result semantics. Nothing critical is missing for an agent to invoke the tool 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 covers both parameters fully (100%), but the description adds required formatting (zero-padded CIK), name resolution behavior, and the interchangeability of type values. It also gives practical examples beyond the schema, justifying a score above baseline.

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 phrasings and states 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from chaining single-pack lookups and conveys a specific verb (profile) and resource (US public company).

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,' giving a clear when-to-use condition and naming the alternative approach. It also provides input format guidance and edge-case handling for private 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

There is substantial overlap among the many question-answering tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, compare_entities, entity_profile, recent_changes) and the prediction-market tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread). While each has nuanced differences, agents will struggle to select the right one, especially with several 'ask_pipeworx' variants that behave nearly identically.

Naming Consistency3/5

Most tool names use snake_case, but patterns vary widely: some are verb_noun (list_feeds, read_feed, subscribe, unsubscribe, remember), others are noun_phrases (polymarket_arbitrage, pipeworx_trending, entity_profile), and a few like 'ask_pipeworx' and 'bet_research' don't follow a consistent structure. The mixed conventions make prediction of new tool names difficult.

Tool Count2/5

With 34 tools, this is far too many for a server named 'Transport Feeds'. The majority of tools are unrelated to transport feeds, covering generic data research, prediction markets, and memory utilities. The count overwhelms any focused purpose and would require extensive discovery to navigate.

Completeness3/5

For the actual data-research and prediction-market functions, the surface is quite complete—covering lookups, comparisons, grounded verification, arbitrage scans, fill risk, trending, and subscriptions. However, for the declared domain (transport feeds), there are only two feed-specific tools (list_feeds, read_feed) with no write/update/delete operations, leaving obvious gaps.

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