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Glama

Regrid

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial behavior beyond that: parallel fan-out across sources, sources_used/sources_failed semantics, empty sections meaning true 'no data', patents API soft-failure, FDA biologics filtering, and name resolution via EDGAR. 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.

Conciseness4/5

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

Long but appropriately so for a tool with many source sections and edge cases. It front-loads the purpose and examples, then densely packs return-field semantics; semicolons and bullet-like clauses keep it scannable without wasted filler.

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?

There is no output schema, so the description correctly carries the full burden. It enumerates every return section (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/failed) and covers input and resolution edge cases. Nothing an agent needs to call it correctly 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?

Schema coverage is 100% and the schema already documents both parameters thoroughly. The description adds the private-company resolved:false behavior and reiterates interchangeable type values — a small but meaningful semantic addition, so a slight boost from baseline is warranted.

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?

States a clear verb+resource: 'full cross-source profile of a US public company in ONE parallel call,' and grounds it with concrete user prompts. It effectively distinguishes itself from the single-pack SEC/XBRL/news lookups it is meant to replace.

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 when to prefer this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also gives clear input routing (ticker, CIK, name) and edge-case behavior (private company returns resolved:false), leaving little ambiguity.

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
Disambiguation3/5

Most tools have detailed guidance, but several sets blur together: ask_pipeworx_beta is currently identical to ask_pipeworx, polymarket_edges and polymarket_arbitrage both scan for opportunities, and discover_tools/suggest_questions both serve discovery. The descriptions are strong enough to prevent frequent misselection, but the boundaries are not always crisp.

Naming Consistency3/5

Names are consistently snake_case, but the stylistic pattern is mixed: verb_noun names like generate_llms_txt and list_subscriptions sit alongside bare verbs like remember/forget and noun-phrase names like entity_profile, recent_alerts, and polymarket_arbitrage. Prefixes like polymarket_*, pipeworx_*, and regrid_parcel_* add some order, but the set is not uniform.

Tool Count2/5

33 tools is well above the point where a tool set remains easy to navigate, and several tools are near-duplicates or wrappers: ask_pipeworx_beta duplicates ask_pipeworx, scan_competitor_ai_presence is a wrapper around ai_visibility_check, and the prediction-market scanners overlap. The broad domain explains some of the bulk, but the surface still feels overweight.

Completeness3/5

The server covers a wide range of workflows: lookup, deep research, claim validation, entity profiles, comparisons, subscriptions, memory, prediction-market analysis, and parcel lookup. However, the Regrid parcel side is thin with only address and point lookup, and there is no direct tool for parcel-ID/owner/sales/tax queries. These are real gaps, though the universal router helps agents work around them.

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