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Glama

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

A4.6/5.0
Behavior5/5

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

The description goes well beyond annotations by detailing fan-out sources, fallback chains (GDELT→GNews), soft-fail behavior for patents, expected empty FDA sections, and the meaning of sources_used/sources_failed. This gives the agent an accurate model of what happens at runtime and what 'no data' means.

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 information-dense, with every sentence contributing a distinct fact about inputs, return sections, or failure semantics. It is front-loaded with user intents and the 'ALWAYS PREFER' guidance before enumerating outputs.

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 multi-source tool with no output schema, the description is remarkably complete: it enumerates every returned section, explains edge cases, defines failure semantics, and covers all accepted input shapes. There is no critical missing context an agent would need to invoke it 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 value by clarifying that type accepts 'company' or 'ticker' interchangeably, giving concrete value examples, and explaining name resolution via SEC EDGAR and the private-company resolved:false case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines a full cross-source profile of a US public company with concrete examples like 'Tell me about X' and 'company profile for Microsoft'. It does not name specific sibling tools, but it does distinguish itself from 'chaining single-pack SEC/XBRL/news lookups', which is enough to establish 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?

The description explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view', which is a clear when-to-use directive. It also specifies accepted input forms (ticker, CIK, company name) and explains behavior for private companies, so agents know how to route requests correctly.

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

A3.8/5.0
Disambiguation2/5

Many tools overlap in purpose: three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are nearly identical routers, five polymarket_* tools cover similar prediction-market ground, and the server combines a tiny Warframe component with a broad Pipeworx/Polymarket toolkit, making selection ambiguous. The server name 'Warframe' does not match the majority of tools, further muddying intent.

Naming Consistency3/5

There is a loose snake_case convention, and several tools follow a verb_noun pattern (get_fissures, list_subscriptions, search_items, validate_claim). However, single-word imperative tools (remember, recall, forget), noun-phrase names (entity_profile, world_state, deep_research), and the polymarket_* family using inconsistent second words break the pattern. It is readable but not cleanly predictable.

Tool Count2/5

35 tools is far too many for a Warframe-focused server, and only 4 tools (get_fissures, get_invasions, search_items, world_state) actually relate to Warframe. The remaining 31 tools are a sprawling generic data/research/prediction-market collection that belongs to a different product, making the set bloated and unfocused for its apparent purpose.

Completeness3/5

Relative to the Warframe domain, the coverage is thin: only fissures, invasions, item search, and a combined world_state are offered, with obvious gaps like alerts, news, Nightwave, and event tracking. The broader Pipeworx/Polymarket toolset is internally comprehensive, but those tools do not serve the server's stated name and leave the Warframe scope incomplete.