team_statsGet team-wide overview statistics: total runs, pass rate, open findings, open incidents, average duration. Supports lifetime, monthly, or weekly periods.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Period filter: "lifetime", "2026-04" (monthly), or "2026-W14" (weekly). Defaults to lifetime. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently lists the output fields and period formats, but does not mention potential caveats like default period behavior (already in schema) or any access/permission requirements. This is adequate for a simple read-only stats tool but lacks depth.
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, front-loaded sentence that lists the key statistics and period support without any filler. Every word earns its place, making it exceptionally concise and scannable.
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 tool with one optional parameter and no output schema, the description enumerates the returned metrics and defines the period argument. Combined with the schema's detailed parameter documentation, this fully covers what an agent needs to understand the tool's scope and invocation. No significant gaps remain.
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 schema already provides 100% coverage for the single 'period' parameter, including examples and a default. The description's mention of 'lifetime, monthly, or weekly periods' adds compatibility but not semantically new information beyond the schema. Per the rubric, high schema coverage yields a baseline of 3.
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 'Get' with a clear resource 'team-wide overview statistics' and enumerates the exact metrics returned. This distinguishes it from sibling tools like target_stats (target-specific) and daily_trends (trends over time), making its purpose unambiguous.
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 the tool's scope ('team-wide') and the supported time periods ('lifetime, monthly, or weekly'), which implies when to use it for team-level overviews. However, it does not explicitly contrast with alternatives like target_stats or mention when not to use it, so it falls short of a perfect score.
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 are clearly separated by resource (targets, runs, findings, incidents, etc.) and action. A few close pairs like active_runs/list_runs and mute_finding/create_muting_rule could confuse, but descriptions clarify the distinctions.
The majority of tools follow verb_noun naming (create_target, get_target, delete_journey). A few outliers use noun phrases (active_runs, daily_trends, system_health, team_stats) which slightly breaks the pattern, but overall the convention is predictable.
74 tools is extreme for any MCP server. Even for a comprehensive monitoring platform, this overwhelms agents with too many granular operations (e.g., enable_all_tests vs disable_all_tests vs update_test, or import_targets duplicating create_target). A more consolidated set would be appropriate.
The tool surface is remarkably complete for the monitoring domain: full CRUD for targets, journeys, rules, reports, secrets, and fragments; plus run triggering, incident management, findings handling, SEO tracking, guest scans, and admin tools. Only maintenance windows lack an update operation, which is minor.