List the calling user's products with denormalized analysis stats.
Paid plans only (basic / pro / enterprise). Free callers get a clear upgrade message.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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?
No annotations are provided, so the description bears full responsibility. It discloses that the tool is read-only (listing) and provides behavior for free users (upgrade message). It also mentions 'denormalized analysis stats' giving insight into the output. This is sufficient 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 two sentences long with no unnecessary words. The first sentence states the main action, and the second provides the key condition. It is front-loaded and efficient.
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?
With 0 parameters and an output schema (not shown), the description covers all necessary context: it lists user's products, includes analysis stats, and notes the paid plan restriction. There are no gaps for an agent to make a decision.
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 tool has 0 parameters, so the baseline is 4. The description does not need to add parameter semantics and correctly focuses on the tool's behavior.
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 it lists the calling user's products with denormalized analysis stats. It specifies the verb 'list' and the resource 'products' with additional detail on the content (denormalized analysis stats). This distinguishes it from sibling tools like 'create_product' and 'get_product'.
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 explicitly states that it is for paid plans only (basic/pro/enterprise) and that free callers receive an upgrade message. This provides clear guidance on when to use the tool, though it does not explicitly mention alternatives for free users.
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.
Each tool targets a distinct resource and action: product lifecycle (create/get/list/update), CVE lookup/search, VEX retrieval, access request, support submission, and identity/quota check. There is no overlap; even create_product and update_product are clearly differentiated by their operation semantics.
All tool names follow a consistent verb_noun pattern (create_product, get_cve, list_products, etc.) using lowercase with underscores. The only outlier is whoami, which is a standard Unix-style command and fits naturally.
10 tools is well-scoped for the domain of Linux kernel security scanning and CVE/product management. Each tool serves a clear purpose without redundancy or bloat, covering the core workflows without overwhelming the agent.
The tool set covers the major lifecycle for products (create, get, list, update) and CVEs (search, get), plus VEX retrieval and account context. Minor gaps exist such as product deletion or direct config upload, but these can be worked around via existing tools and the REST API.
