lambda_list_firewall_rulesList the account's inbound firewall rules (protocol, port range, source CIDR, description). Lambda Cloud REST: GET /api/v1/firewall-rules.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
The annotation readOnlyHint=true already declares this a read operation, so the description doesn't need to repeat that. It adds useful context about the scope and returned fields, but does not disclose potential pagination, rate limits, or authentication requirements, which would make the behavior more transparent.
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 one sentence, front-loaded with the verb and resource, followed by a compact field list and an API endpoint reference. Every element adds value and there is no redundancy or filler.
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 parameterless list tool with a readOnly annotation, the description adequately covers the resource scope and the main output fields. It omits details like pagination or response envelope, which would make it more complete, but the core intent and return content are clear.
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 zero parameters and the input schema is empty with 100% coverage, so there is no parameter semantics to document. The parenthetical list describes output fields, not parameters, and the 0-parameter baseline of 4 applies.
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 uses a specific verb ('List') and a specific resource ('the account's inbound firewall rules') with a parenthetical field list. This clearly distinguishes it from sibling tools like lambda_list_firewall_rulesets and lambda_get_firewall_ruleset, which target rulesets rather than the rules themselves.
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 clearly states it lists the account's inbound firewall rules, which gives an agent the context to select it for that purpose. However, it does not explicitly call out when not to use it or mention the ruleset-related alternatives, leaving the distinction to the sibling tool names.
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 (e.g., list_instances vs. launch_instance vs. terminate_instances). There is no overlap or ambiguity between tools; even similar resources like firewall_rules and firewall_rulesets are clearly differentiated by name and description.
All tool names follow the verb_noun pattern with the lambda_ prefix, using lowercase and underscores consistently. The verb clearly indicates the operation (list, get, create, delete, launch, update, restart, terminate), and the noun indicates the resource. Minor pluralization differences (e.g., list_instances vs. get_instance) are conventional and do not break consistency.
15 tools is well-scoped for a GPU cloud management server, covering instances, filesystems, firewall rules, images, instance types, and audit events. Each tool serves a distinct purpose and no unnecessary duplication exists.
The instance lifecycle is well covered with launch, get, list, update, restart, and terminate. Filesystem and firewall read operations are present, but firewall rule/ruleset management (create/update/delete) is missing, which is a minor gap that may require working around via the dashboard.