Company financial-health scan (bundle) — One call: a public company's revenue & margin trend, current ratio, profitability and recent material filings (8-K/10-K/10-Q) fused into a healthy/watch/distress verdict. Ticker or CIK. SEC EDGAR. JSON. Price: $0.05 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ticker (AAPL) or 10-digit CIK |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only and non-destructive behavior. The description adds meaningful context beyond those annotations: it performs a bundled multi-part scan, pulls from SEC EDGAR, returns JSON, and costs $0.05 USDC via x402. This is useful operational transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence with no wasted words. It front-loads the purpose and output, then packs input, source, format, and price into a compact, scannable form.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema, the description covers everything needed to call it correctly: input type, data source, return format, pricing, and the nature of the output verdict. Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the single parameter with the ticker example and 10-digit CIK format. The description merely repeats 'Ticker or CIK,' adding no new semantic detail beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource (public company), the data inputs (revenue/margin trend, current ratio, profitability, material filings), and the distinctive deliverable (healthy/watch/distress verdict). This distinguishes it from filing-specific tools like sec_filings_search and general snapshots like sec_company_snapshot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The 'bundle' and 'One call' phrasing imply this is the consolidated tool for a financial-health verdict, and it clearly gives the input forms (ticker or CIK). However, it never names sibling tools or states when to choose this over finance_company_360, finance_peer_compare, or sec_filings_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.
Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.
50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.
For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.