Read saved dashboard views. No id → list all: [{ id, name, isDefault, rev, editedBy }]. With id → that view's full layout + rev (pass this rev as the CAS base to configure_dashboard update). Views are both agent- and human-editable; write them with configure_dashboard.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Omit to list every saved view (summary); pass a view id for its full layout + rev. |
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 readOnlyHint annotation already declares it read-only. The description adds detailed return structure (list summary vs. full layout + rev) and explains the rev field's role in updates via configure_dashboard, exceeding the annotation baseline.
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, front-loaded with purpose, and every sentence adds unique value. No redundancy or waste.
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?
Given the tool's simplicity (one optional parameter, no output schema), the description fully covers behavior, return structure, and relationship with sibling tool. Nothing significant 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?
Schema covers the id parameter with 100% description coverage. The description adds context by explaining the rev usage for updates, providing extra value beyond the schema.
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 reads saved dashboard views and distinguishes two modes: list all without id, and get full layout with id. It also differentiates from the sibling configure_dashboard tool by stating it is for writing.
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 specifies when to use each mode (no id vs. with id) and points to configure_dashboard for writing. It could be stronger by explicitly stating when not to use it, but the context is sufficient.
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.
Most tools have distinct purposes, but pause/pause_all and metrics/campaign_results/list_campaigns have overlapping scopes. Descriptions clarify the differences, so ambiguity is low.
Uses snake_case with a mix of verb_noun (list_campaigns) and noun_verb (infrastructure_status), but patterns are predictable. Minor inconsistency between setup_infrastructure and infrastructure_status.
25 tools is at the upper bound for a focused server, but the domain (cold email automation) justifies the number. Each tool covers a distinct aspect of the workflow.
Covers account management, campaigns, leads, threads, infrastructure, webhooks, and dashboards. Missing resume for paused campaigns and delete for campaigns, but core operations are present.