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Glama

colorapi

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. Added

TDQS

A5/5.0
Behavior5/5

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

Goes far beyond the annotations (readOnly, idempotent, openWorld) by detailing what each return section means, including edge cases like FDA products being empty for generic-only companies and patents soft-failing after May 2025. Explicitly states that empty sections are real 'no data' and not bugs, and explains sources_used/sources_failed semantics. No contradiction 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Although long, every sentence carries information. The structure front-loads example queries, lists return sections concisely with parenthetical clarifications, and handles edge cases in-line. No filler or redundancy. The length is appropriate for the tool's complexity.

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?

The description covers all aspects that an agent needs: input variants, return fields (cik, filings, fundamentals, patents, etc.), failure modes (empty sections, private companies, patent API sunset), and the meaning of sources_used/sources_failed. With no output schema, the description fully compensates by detailing return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, giving both parameters full descriptions. The description adds value by explaining that 'type' accepts company or ticker interchangeably and that 'value' can be any of three forms. It also clarifies that names resolve via SEC EDGAR matching, which is not obvious from the schema alone.

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 states a clear verb+resource: produces a 'full cross-source profile of a US public company in ONE parallel call.' It enumerates the exact sources and return sections, distinguishing it from siblings like compare_entities and resolve_entity. The opening example queries make the purpose immediately recognizable.

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 instructs to 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' Provides input formats (ticker, CIK, name) and clarifies when it will not resolve (private companies yield resolved:false). No sibling exclusion is needed because the scope is clearly defined.

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

A4/5.0
Disambiguation3/5

Some tools have distinct purposes (e.g., color tools, memory tools), but many data query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) overlap significantly, making it hard for an agent to choose the right one without deep knowledge of their nuances.

Naming Consistency4/5

Most tool names use snake_case with a verb_noun pattern (e.g., convert_color, identify_color, resolve_entity), but there is inconsistency in prefixes: some use 'ask_pipeworx', others 'pipeworx_', 'polymarket_', or 'scan_'. Overall, still readable and predictable.

Tool Count3/5

33 tools is on the high side for a single server, especially one named 'colorapi' which misleadingly suggests a focus on color only. The tool count is borderline appropriate for the actual broad data integration scope, but the mismatch with the server name is problematic.

Completeness4/5

The tool set covers a wide range of data sources and operations (SEC, FDA, patents, news, Polymarket, memory, subscriptions), with few obvious gaps. Minor lacks: no direct tool for updating stored memories or handling non-US companies, but overall comprehensive.

Resources