Return uptime and SLO metrics for the MCP service.
| Name | Required | Description | Default |
|---|---|---|---|
| admin_token | Yes | Admin authentication token. Must match ADMIN_TOKEN environment variable. | |
| window_hours | No | Time windows in hours for the report. Default: [24, 168] (24h + 7d). |
| Name | Required | Description | Default |
|---|---|---|---|
| p50 | No | ||
| p95 | No | ||
| uptime | Yes | ||
| window | No | ||
| errorRate | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds context about what the tool returns (uptime and SLO metrics) and names the service (MCP service), which is useful beyond annotations. No contradiction with annotations, and the description provides meaningful behavioral context.
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, concise sentence (10 words) that efficiently states the tool's function. It is front-loaded with the key verb and resource, with zero redundant or filler content. Every word earns its place.
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 has only 2 parameters (both well-documented in schema), an output schema exists (so return format isn't the description's job), and annotations provide read safety, the description is largely complete. It could mention that window_hours is optional and defaults to [24, 168], but the schema already covers this, so the completeness is adequate for the tool's simplicity.
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 description coverage is 100%, so the schema already documents both parameters well. The description does not add parameter details beyond the schema, but since coverage is high, baseline is 3. The description mentions 'uptime and SLO metrics' which implies the outputs and justifies the window_hours parameter, earning a slight bonus to 4.
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 verb 'return' and the specific resource 'uptime and SLO metrics for the MCP service'. It is unambiguous but does not explicitly distinguish from siblings like health_check, which also returns service status. The title 'SLO Report' reinforces the purpose.
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 provides no guidance on when to use this tool versus alternatives such as health_check (which likely also returns uptime info). It does not specify when not to use it or mention prerequisites like needing admin_token. The context is implied by the tool's purpose but lacks explicit direction.
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.
Several tools are redundant: recall_memory is explicitly an alias of recall, and save_memory/save_to_synapse/store_memory all persist memories. This makes the tool boundary unclear for agents choosing between them, even though core operations like health_check and slo_report are distinct.
Names are consistently snake_case, but verb usage is inconsistent: save_memory, save_to_synapse, and store_memory use different verbs for the same operation, and recall/recall_memory add an alias rather than following one convention. The pattern is readable but not predictable.
Thirteen tools is not inherently excessive for an agent-memory/trust service, but the presence of multiple aliases inflates the surface and means not every tool earns its place. The effective set is smaller, making the count feel padded.
The surface covers initialization, save, list, search/recall, feedback, and handover, but there is no update or delete operation for memories. This leaves lifecycle management incomplete and may force agents to work around missing state-management operations.
