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Glama

Mhw

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

A4.8/5.0
Behavior5/5

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

Annotations only declare readOnly/openWorld/idempotent; the description adds substantial behavioral context: fan-out across multiple data sources, USPTO soft-fail after API sunset, GDELT→GNews fallback, empty sections meaning real 'no data', sources_used/sources_failed, and resolved_from/resolved_to behavior. This far exceeds what annotations alone convey.

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 front-loaded with usage examples and core purpose, and every section of detail serves a real need. It is dense and long, but the density comes from genuinely important behavioral specifics rather than 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?

For a complex tool with no output schema, the description covers expected return sections, source failure semantics, empty-result meaning, fallback behavior, and edge cases for private companies and name resolution. An agent has everything needed to invoke and interpret results correctly.

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 the baseline is 3. The description adds meaningful operational nuance by clarifying that 'company' and 'ticker' are interchangeable, that value can be a ticker, CIK, or name, and that names resolve via SEC EDGAR match. It doesn't restate schema but enriches it.

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 exemplar queries and defines a specific verb+resource: creating a full cross-source profile of a US public company in one parallel call. It explicitly contrasts itself with chaining single-pack SEC/XBRL/news lookups, giving the tool a clear identity.

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 includes an explicit 'ALWAYS PREFER over chaining single-pack lookups' instruction and the trigger condition ('when the user asks for a holistic view'). It also covers the edge case of private companies returning resolved:false, which tells the agent what to expect rather than leaving it to guess.

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

B3.3/5.0
Disambiguation2/5

Several tool groups heavily overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all route to the same 5,798-tool catalog and compete for the same 'answer this question' use case. The Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker) also all detect betting opportunities, making it easy to pick the wrong one.

Naming Consistency2/5

Naming conventions are mixed: verb_noun (ask_pipeworx, compare_entities, validate_claim), noun_noun (entity_profile, polymarket_arbitrage), adjective_noun (recent_changes, deep_research), and get_* for the MHW tools. All names use snake_case, but there is no consistent structural pattern across the set.

Tool Count2/5

35 tools is too many for a coherent server, and the bulk of them (31 tools) are unrelated to the server's apparent 'Mhw' identity, which covers only 4 Monster Hunter World tools. The set reads like three separate servers (MHW game data, Pipeworx research, Polymarket betting) merged into one.

Completeness1/5

For a server named 'Mhw', the MHW surface is severely incomplete: armor, monsters, skills, and weapons exist, but quests, items, decorations, crafting, and locations are missing. The non-MHW tools are broad but belong to a different domain, so the server does not come close to covering its apparent intended purpose.

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