Get Run Details
get_runGet full details of a specific test run including metrics, score, summary, errors, and associated findings.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| runId | Yes | The run ID |
get_runGet full details of a specific test run including metrics, score, summary, errors, and associated findings.
| Name | Required | Description | Default |
|---|---|---|---|
| runId | Yes | The run ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the transparency burden. It does list the included data fields, which provides some insight into return contents, but it does not mention error handling, permissions, or explicitly state that it is a read-only operation. 'Get' implies read-only but this is not stated.
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 with no filler. It states the action, the target resource, and the expected content in a compact and readable way.
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?
The tool has one simple parameter and no output schema, so the description need not explain return types. It adequately communicates the main output (metrics, score, summary, errors, findings) and the target resource. However, it could have explicitly mentioned that the runId is required to specify which run, though the schema already conveys this.
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 provides full coverage for the single parameter runId with the description 'The run ID'. The tool description adds no parameter-specific information, so baseline 3 is appropriate.
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') and resource ('specific test run'), clearly distinguishing it from sibling list_runs. It also lists the contents (metrics, score, summary, errors, findings), which makes the tool's 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?
There is no explicit when-to-use or when-not-to-use guidance, nor any mention of alternatives. The usage is implied as a standard getter for full run details, but the description does not provide exclusions or comparisons with sibling tools like list_runs.
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.