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Color

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
Behavior4/5

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

Annotations already mark it as readOnly, idempotent, and non-destructive. Description adds that it fans out across multiple sources in one parallel call, returns specific fields like recent_filings with URIs, and notes that the USPTO source may soft-fail. No contradictions with 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 fairly long but front-loads with example queries and packs each sentence with useful information. Could be slightly more structured with bullet points, but every sentence earns its place. No unnecessary repetition.

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 no output schema, description details what each returned field contains (e.g., up to 5 filings, fundamentals sorted, etc.). It also notes limitations (USPTO may soft-fail). Could mention any pagination or max results beyond what's implied, but overall provides sufficient context for an agent to use 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?

Schema coverage is 100%. Description adds context: 'type' only supports 'company', 'value' must be ticker or zero-padded CIK, and names are not supported. It also provides examples like 'AAPL' and '0000320193', clarifying usage beyond schema definitions.

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?

Description uses specific verbs like 'Tell me about', 'research', 'brief me' and clearly states it provides a 'full cross-source profile of a US public company' across multiple data sources. It lists exactly what is returned (CIK, filings, fundamentals, patents, news, LEI) and distinguishes from sibling tools like resolve_entity.

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 says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' Also states that names are not supported and advises using resolve_entity first if only a name is available. Provides clear when-to-use and when-not-to-use guidance.

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

A3.9/5.0
Disambiguation2/5

Several tools are near-identical: ask_pipeworx and ask_pipeworx_beta are explicitly the same right now, and the three ask_pipeworx variants plus deep_research all route the same underlying catalog. The six polymarket_* tools also have heavily overlapping purposes, requiring deep reading to choose correctly. Most other tools are distinguishable, but these clusters create real misselection risk.

Naming Consistency3/5

The set is uniformly snake_case and mostly descriptive, with consistent micro-families like remember/recall/forget and polymarket_*. However, there is no single convention across the server: verb_noun names (ask_pipeworx, list_subscriptions) mix with noun-first names (entity_profile, bet_research, nearest_color), and the Pipeworx brand is used as both prefix and suffix. Readable but inconsistent.

Tool Count2/5

At 34 tools, the surface is far larger than a typical well-scoped server, and the count is especially unjustified for a server named 'Color' where only three tools relate to that name. The breadth stems from bolting a full data-research platform, prediction-market suite, memory store, and subscription system onto what appears to be a simple utility. Too heavy.

Completeness4/5

For the dominant Pipeworx research domain, the set is unusually thorough: query, grounded verification, deep research, entity resolution, comparisons, claim validation, change feeds, subscriptions, alerts, memory, and discovery are all present. Minor gaps exist (e.g., no direct account management tool, and color coverage only includes convert/contrast/nearest with no palette generation), but these are workaround-able. Completeness is strong for the real domain, if mismatched with the server name.

Resources