Insider trading activity (bundle) — One call: recent SEC Form 4 insider transactions for a public company — who bought/sold, share counts and dollar value over the last ~120 days, netted into a bullish/bearish/neutral insider signal. 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 indicate this is read-only and non-destructive. The description adds valuable behavioral context by revealing it is a bundled one-call API, uses SEC EDGAR, returns JSON, costs $0.05 USDC via x402, and produces a synthesized insider signal. This goes beyond what the 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense with useful facts—time window, data source, output fields, signal type, pricing, and payment rail—without filler. Each segment earns its place, and the key scope statement is front-loaded.
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 single-parameter tool with no output schema, the description covers the essential context: input format, time range, data source, contents of the result, signal synthesis, and cost. It does not spell out the exact JSON response shape, but the level of detail is sufficient for an agent to invoke it correctly.
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 only parameter, id, is already fully described in the schema as 'ticker (AAPL) or 10-digit CIK', which matches the description's mention of 'Ticker or CIK'. Since schema coverage is 100%, the description adds little semantic value beyond what the input 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 clearly states the tool returns recent SEC Form 4 insider transactions for a public company, including who bought/sold, share counts, dollar value, and a netted bullish/bearish/neutral signal. This distinguishes it from broad SEC filing search tools and company financial tools among the siblings.
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 description gives clear context for when to use the tool: when recent insider trading activity over the last ~120 days is needed, accepting a ticker or CIK. It does not explicitly name alternative tools or state when not to use it, but the input scope and purpose are sufficiently clear for an agent 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.
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.