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Glama

dnd5e

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

A4.9/5.0
Behavior5/5

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

Although annotations already mark the tool as read-only and idempotent, the description adds substantial behavioral context: it fans out across SEC, XBRL, USPTO, USAspending, FDA, DOL, news, and GLEIF; explains that empty sections mean real 'no data'; discloses the USPTO PatentsView API sunset with soft-failure behavior; and clarifies that private companies return resolved:false with an explicit notes line. None of this contradicts the 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?

The description is long, but the tool is genuinely complex with many data sources and edge cases. It front-loads the purpose and triggers before listing outputs and source semantics. Some sentences are dense and could be trimmed, but each section earns its place for such a comprehensive tool.

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 tool has no output schema and the task is broad, the description is unusually complete: it enumerates every returned field group, explains source-level failure modes, covers input type flexibility, and gives explicit guidance for expected empty results. An agent can accurately predict behavior and formulate a call without additional context.

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?

Schema description coverage is 100%, and the description goes beyond the schema by noting 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 private-company fallback, which adds real operational meaning not present in the schema alone.

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 names a specific verb and resource: building 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,' making it easy for an agent to select this tool over the general category of piecemeal lookups.

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 gives concrete trigger phrases ('Tell me about X', 'research Acme', 'brief me on Tesla') and an explicit directive to prefer this over chaining single-source calls when a holistic view is requested. It also covers edge cases like private companies and how to pass inputs, so an agent knows both when and how to invoke it.

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

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as the three ask_pipeworx variants, the memory tools (remember/recall/forget), and the subscription management tools. Additionally, the D&D tools are mixed with a large set of unrelated tools, causing confusion between domains.

Naming Consistency2/5

Naming conventions are inconsistent: some tools follow verb_noun pattern (e.g., get_class, list_spells), while others use descriptive noun phrases (e.g., ai_visibility_check, polymarket_arbitrage). There is no clear, predictable pattern across the set.

Tool Count2/5

With 35 tools, the count is high for a server ostensibly focused on D&D 5e. The inclusion of many unrelated tools from the Pipeworx ecosystem makes the set feel bloated and unfocused for the intended domain.

Completeness1/5

For the D&D 5e domain, only 4 tools exist (get_class, get_monster, get_spell, list_spells), which is severely incomplete. The remaining tools cover other domains, but they do not serve the server's primary purpose, leaving obvious gaps in functionality.

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