list_targetsList all monitoring targets for your team. Returns name, URL, type, status, and uptime info for each target.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by target type | |
| limit | No | Max number of targets to return | |
| status | No | Filter by target status |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It does disclose the return fields (name, URL, type, status, uptime), but it does not disclose that the limit parameter caps the result set, making the word 'all' potentially misleading. There is also no mention of pagination or other behavioral nuances.
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 concise sentences that are front-loaded with the action and immediately state the return contents. Every word is informative, 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 simple list tool with three optional parameters, the description covers the essential return fields, but it omits that the default limit of 50 may prevent returning 'all' targets. It also does not clarify how filtering by type/status interacts with the result set, though the schema provides parameter details. The lack of an output schema makes the return-field disclosure useful, but the 'all' wording creates a completeness gap.
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 descriptions cover 100% of the parameters (type, limit, status) with clear semantics, so the baseline is 3. The description does not add any parameter-related meaning beyond what the schema already provides; it only mentions return fields, which are not parameters.
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 the specific verb 'List' and a clear resource ('monitoring targets for your team'), making the operation unambiguous. It distinguishes itself from sibling tools like get_target (single target), create_target, and delete_target by clearly indicating a bulk read operation.
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. It does not mention that get_target should be used for a single target, or that list_tests handles a different resource, nor does it state any exclusions or prerequisites. The reader must infer usage from the tool name and schema.
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.