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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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly and idempotent, so safety is covered. Description adds context on soft-fail of USPTO API and parallel fan-out behavior, which is valuable beyond 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?

Description is a single dense paragraph with no wasted words, front-loaded with examples. Slightly long but every sentence adds value, earning a high score.

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?

Given the rich annotations and complete schema, the description adequately details return fields and data sources. No output schema, but the description compensates with specific field names and notes about USPTO sunset.

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?

Schema coverage is 100% with clear parameter descriptions. Description reiterates that value accepts ticker or CIK and that names are unsupported, providing marginal extra clarity but no new semantics.

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 clearly states it provides a 'full cross-source profile of a US public company in ONE parallel call' and lists specific data sources and return fields. It distinguishes from siblings by promoting itself over chaining single-pack lookups.

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?

Explicitly gives example queries for when to use ('Tell me about X', 'research Acme'), states preference over chaining single-pack lookups, and specifies when not to use (names not supported, use resolve_entity first).

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

Many tools have overlapping purposes, especially the various ask_pipeworx variants and entity research tools (entity_profile, compare_entities, recent_changes). The subtle differences between ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are likely to cause agent misselection.

Naming Consistency2/5

Tool names use inconsistent patterns: snake_case (ask_pipeworx, query_layer) mixed with descriptive phrases (ai_visibility_check, generate_llms_txt) and no clear verb_noun structure. Some names are vague (process, run) though those are absent here; overall naming is arbitrary.

Tool Count2/5

34 tools is too many for an Arcgis Tigard server. The majority are generic Pipeworx data query tools (27+ tools) that have little to do with ArcGIS, making the tool count feel bloated and unfocused for the server's stated purpose.

Completeness1/5

The server severely lacks ArcGIS-specific functionality. Only three tools (search_datasets, query_layer, layer_info) are relevant to ArcGIS; the rest are unrelated Pipeworx tools. Essential ArcGIS operations like editing, analysis, or visualization are missing, making the surface incomplete.