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Glama

Qrcode

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

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description adds substantial behavioral context: parallel fan-out across sources, soft-fail for the sunsetting USPTO PatentsView API, expected-empty semantics for fda_products, and the meaning of sources_used/sources_failed. It also clarifies that empty sections are real no-data outcomes, not bugs. No contradiction with annotations exists.

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 nearly every clause carries operational information such as API sunset dates, URI formats, resolved_from/resolved_to, and expected-empty edge cases. It front-loads the common user intent and the routing preference before diving into field details. Minor redundancy with the schema's type explanation keeps it from a perfect 5.

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 must carry the return contract, and it does: it enumerates returned fields, source coverage, URI formats, fallbacks, and failure semantics. It also covers input edge cases like private companies and zero-padded CIKs. For a tool with this much cross-source complexity, nothing critical is 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?

The input schema already documents both parameters with 100% coverage, so the baseline is 3. The description adds valuable examples ("AAPL", "0000320193", "Moderna"), clarifies that type accepts "company" or "ticker" interchangeably, and explains that names resolve via SEC EDGAR. This goes beyond the schema but is not entirely essential given the schema's already strong 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?

The description opens with natural-language examples and defines the tool precisely as a "full cross-source profile of a US public company in ONE parallel call," listing the source systems and key returned sections. It differentiates itself from simpler lookups by explicitly stating it should be preferred over chaining single-pack SEC/XBRL/news calls. This is a specific verb+resource+scope statement, not a tautology.

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?

The description gives a clear when-to-use rule: "ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view." It also details acceptable input forms and the private-company fallback behavior. It does not name sibling tools like resolve_entity or deep_research or state explicit when-not conditions, so it stops short of a perfect 5.

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

Several tool families blur together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to the same underlying data sources for slightly different modes, and the six polymarket_* tools plus bet_research all orbit prediction-market opportunity-finding. The descriptions are detailed, but an agent would need to read deeply to reliably distinguish them.

Naming Consistency3/5

Names are all readable snake_case and some clusters are consistent (ask_pipeworx*, polymarket_*, pipeworx_*), but the set mixes verb-first names like create_qr and validate_claim with noun-first names like entity_profile, recent_alerts, polymarket_edges, and pipeworx_trending. There is no single predictable naming convention.

Tool Count2/5

33 tools is above the 25+ threshold and reads as a full platform rather than a focused tool. For a server labeled Qrcode, only two tools are QR-related, so the count is severely inflated even if the data-research breadth is defensible.

Completeness2/5

The Pipeworx data-research surface is fairly complete: query, grounded verification, entity profiling, comparisons, recent changes, discovery, memory, and subscriptions are all represented. But the QR domain for the stated server purpose is only create/read with no batch, styling, or management, and the overall set has no coherent domain to be complete against.

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