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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?

Annotations already show readOnly/openWorld/idempotent/non-destructive behavior, but the description adds substantial context: parallel fan-out across sources, soft-fail behavior for the USPTO patents API, semantics of sources_used/sources_failed, empty sections meaning real "no data," and private-company behavior. This goes well beyond 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 it is front-loaded with usage examples and an explicit preference statement. Every section earns its place because there is no output schema, so the description must document return fields and failure semantics; still, it could be tightened.

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 no output schema, the description fully compensates by enumerating the major return sections, source-specific behaviors, expected empty results, resolution semantics, and accepted input shapes. It covers all the information an agent needs to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and both parameters already document ticker/CIK/name inputs and the interchangeable type behavior. The description repeats most of this and adds only marginal output-focused context, such as private-company resolution behavior, which is more behavioral than parameter-specific.

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 states a specific verb and resource: "full cross-source profile of a US public company in ONE parallel call," backed by concrete example queries. It also differentiates itself by explicitly preferring this tool over "chaining single-pack SEC/XBRL/news lookups," which separates it from narrower sibling tools.

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 to use this tool when the user asks for a holistic view and to always prefer it over chaining multiple single-pack lookups. It also covers edge-case routing: names resolve via SEC EDGAR, and private companies return resolved:false with an explicit notes line rather than a bare failure.

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

A3.6/5.0
Disambiguation3/5

Most tools are clearly distinct, but there are several overlapping clusters: ask_pipeworx and ask_pipeworx_beta are near-duplicates today, the Polymarket tools (edges, arbitrage, fill_risk, bet_research) have partially overlapping discovery purposes, and ai_visibility_check vs scan_competitor_ai_presence overlap on single vs multi-entity checks. These overlaps create real misselection risk, though the rest of the set splits cleanly.

Naming Consistency3/5

All names are snake_case and readable, but conventions vary noticeably: verb_noun for actions (check_ip, report_ip, list_subscriptions), domain-prefixed nouns for the Polymarket cluster (polymarket_edges, polymarket_arbitrage), and brand-prefixed meta tools (ask_pipeworx, pipeworx_feedback). Subfamilies are internally consistent, but the overall set mixes patterns.

Tool Count2/5

34 tools is already past the heavy threshold, but the bigger issue is the server name: Abuseipdb should have a handful of IP-abuse tools, yet only 3 of 34 actually relate to AbuseIPDB. The remaining 31 tools form an unrelated Pipeworx/Polymarket/memory suite, making the count wildly inappropriate for the apparent purpose.

Completeness2/5

For the declared AbuseIPDB domain, only check, report, and blacklist are covered; obvious gaps remain like removing/clearing a false report, bulk IP checks, or category metadata. The broader set is a grab bag of unrelated capabilities, so no single domain gets complete lifecycle coverage, and the nominal AbuseIPDB surface is thin and diluted.