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Glama

Jsonschema

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. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Discloses non-obvious behaviors: USPTO PatentsView API sunset soft-fail, empty sections being real 'no data' rather than errors, private companies returning resolved:false with notes, and `type` accepting 'company' or 'ticker' interchangeably. Annotations already cover read-only/idempotent safety, and the description meaningfully adds beyond-annotation context.

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 every section contributes: examples, core value proposition, source list, output fields, and failure/edge-case semantics. Since there is no output schema, the length is justified and the most important directive ('ALWAYS PREFER...') is front-loaded.

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?

For a multi-source tool with only 2 schema-documented parameters and no output schema, the description is exceptionally complete. It covers input resolution, all return sections, source failure modes, empty-section semantics, and private-company behavior. No essential information for correct invocation appears missing.

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%, so baseline is 3. The description adds valuable detail: accepted input shapes (ticker, zero-padded CIK, company name), example values, and the note that both `type` values behave identically. This goes beyond the schema's own parameter descriptions.

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 states it returns a 'full cross-source profile of a US public company in ONE parallel call,' enumerating specific sources and output fields. It clearly differentiates itself from chaining single-pack SEC/XBRL/news lookups and from siblings like compare_entities by scoping to a single entity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides concrete example intents ('Tell me about X', 'research Acme') and explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It gives clear when-to-use context, though it does not explicitly contrast with sibling tools like deep_research or compare_entities.

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

A3.8/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same routing and response shape, while the polymarket_* family and company-research tools (entity_profile, compare_entities, recent_changes) have overlapping triggers. The descriptions are detailed, but an agent can still easily select the wrong variant.

Naming Consistency3/5

Names are readable and consistently snake_case, with recognizable families like ask_pipeworx_*, polymarket_*, and pipeworx_*. However, conventions mix verb_noun patterns (compare_entities, resolve_entity) with noun phrases (entity_profile, recent_alerts, pipeworx_trending), so the pattern is not fully consistent.

Tool Count2/5

32 tools is heavy for any single server, and nearly all of them are unrelated to the 'Jsonschema' name—only validate_json_schema actually addresses JSON Schema. Even viewed as a Pipeworx data/research toolkit, the set feels bloated with near-duplicate query and prediction-market variants.

Completeness2/5

If the intended domain is JSON Schema, the surface is severely incomplete: only validation exists, with no parsing, generation, or schema-management tools. If the intended domain is the Pipeworx data-research suite, it is more complete but still lacks a raw record-fetch tool despite citations promising pipeworx:// URIs, and the server-name mismatch creates a confusing dead end.

Resources