List your agents — List all agents owned by the authenticated user. Supports pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many agents to return, 1-100. | |
| offset | No | How many agents to skip, for pagination. |
| Name | Required | Description | Default |
|---|---|---|---|
| scope | Yes | Echoes the resolved listing scope. | |
| agents | Yes | The caller's agents, reduced to the MCP trust-loop field set. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds the scope constraint ('owned by the authenticated user') and pagination support, which is helpful. However, it does not disclose ordering, error cases, or rate limits, so it only moderately adds beyond annotations.
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?
Two sentences, front-loaded with the action and resource, then a clarifying detail. Every word earns its place; there is no fluff or redundancy. The dash separator improves readability.
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?
With high annotation coverage, a fully described input schema, and an existing output schema, the description is complete for a simple read-only list operation. It correctly mentions pagination and the ownership scoping, which are the only non-obvious aspects beyond the structured data.
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%, with both limit and offset parameters already fully described in the schema. The tool description only says 'Supports pagination,' which adds no additional meaning beyond the schema. Baseline of 3 is appropriate because the schema carries the parameter documentation burden.
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?
Description uses a specific verb and resource: 'List your agents — List all agents owned by the authenticated user.' It clearly distinguishes from sibling tools like get_agent (which fetches a single agent) and claim_agent (which assigns ownership). The scope is explicit and 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 states it lists agents owned by the authenticated user and supports pagination, providing clear context for when to use this tool. It does not explicitly name alternatives or exclusions, but the sibling list hints at differentiated use cases. A stronger statement like 'use this instead of get_agent for all agents' would earn a 5.
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.
Each tool targets a distinct operation: identity claiming, lookup, reputation retrieval/badge, scanning, verification, alignment/protection management, and feedback. No significant overlap exists.
All tools follow a consistent verb_noun pattern using snake_case (e.g., claim_agent, get_reputation, verify_scan). Even complex names like preview_compose_alignment_by_agent adhere to the pattern.
With 16 tools, the set is slightly heavy but still well-scoped for the domain of AI agent trust ratings. Each tool serves a clear purpose, and no tool feels redundant.
The surface covers core workflows: agent identity, reputation, alignment/protection, scanning, verification, and feedback. Minor gaps like agent updates or deletion might exist, but the core lifecycle is complete.
