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Glama

Caniuse

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

A5/5.0
Behavior5/5

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

Despite annotations already declaring readOnly/openWorld/idempotent/destructive hints, the description adds substantial operator-relevant behavior: source fallbacks, soft-failures for the sunsetting USPTO API, empty sections meaning real 'no data', and resolved_from/resolved_to behavior for name inputs. It also pre-empts false-error interpretation with 'an empty section is a real "no data", not a bug.'

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?

The description is long, but every sentence earns its place: no output schema exists, so the detailed return-structure and failure-mode documentation is necessary rather than redundant. It is front-loaded with examples and the core purpose before diving into specifics.

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?

Given the lack of an output schema, this description is remarkably complete: it lists every data section, explains what each contains, covers expected empty results, names fallback chains, describes input permutations, and states the private-company behavior. An agent has enough context to invoke the tool correctly and interpret its results.

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?

Even though schema coverage is 100%, the description goes beyond by clarifying that 'type' accepts 'company' or 'ticker' interchangeably and that 'value' can be a ticker, zero-padded CIK, or company name. It also explains name resolution via SEC EDGAR and the resolved:false result for private companies, adding meaning the schema alone does not provide.

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 concrete user phrasings and states a specific action: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from chained single-source lookups and even names the exact input types accepted, leaving no ambiguity about what the tool does.

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?

It explicitly instructs to 'ALWAYS PREFER' this tool over chaining single-pack SEC/XBRL/news lookups when a holistic view is requested. It also covers exclusions: private companies return resolved:false, and 'person/place coming soon' signals current scope is limited to companies.

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

The tool set has significant overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and deep_research, entity_profile, compare_entities, recent_changes, and validate_claim all retrieve structured data with overlapping capabilities. The five Polymarket-oriented tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) further blur boundaries. Agents will struggle to select the right tool without reading very long descriptions.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern (ask_pipeworx, compare_entities, validate_claim), and the polymarket_* cluster is consistently prefixed. However, a few tools are bare nouns (feature, support, search) and the remember/forget/recall trio deviates from the dominant pattern, creating minor inconsistency.

Tool Count2/5

35 tools is excessive for a server named 'Caniuse' — only 4 tools actually pertain to browser compatibility (feature, support, search, list_browsers), while 31 are Pipeworx data tools. The server name misrepresents the content, and the sheer number overwhelms rather than scopes the surface.

Completeness3/5

For the caniuse domain, coverage is complete (search, feature, support, list_browsers). The Pipeworx side includes meta-tools (discover_tools, suggest_questions), retrieval, memory, subscriptions, and feedback, but some tools require accounts and there are gaps like no direct way to list all data sources without discover_tools. The overall surface is broad but lacks obvious missing operations for any single coherent domain.

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