route_reputation_skillReturns exactly one of Agentic Substrate training, reputation creation, or reputation maintenance and renewal without registering, messaging, or submitting anything.
| Name | Required | Description | Default |
|---|---|---|---|
| skill | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds value by specifying 'without registering, messaging, or submitting anything' and guarantees 'exactly one' result, reinforcing the read-only nature in domain-specific terms. No contradiction with 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?
The description is a single, front-loaded sentence that clearly states the core behavior and limitation. Every word earns its place, with 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 tool with one enum parameter and rich annotations, the description is nearly complete. It explains the return value ('exactly one of...') and the lack of side effects. Minor gap: it does not explicitly state the output format (e.g., that it returns the skill string directly), but this is strongly implied.
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 coverage is 0%, so the description must compensate. It lists the three possible values in natural language: 'Agentic Substrate training, reputation creation, or reputation maintenance and renewal', which maps directly to the enum. This adds meaning beyond the bare schema by providing descriptive labels and clarifies the sole parameter's purpose.
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 tool's function: it returns exactly one of three specified reputation-related skills. It distinguishes from siblings by explicitly noting the absence of side effects ('without registering, messaging, or submitting anything'), which aligns with the title and separates it from tools like learn_reputation or route_valve.
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 implies a use case (pure routing decision without side effects) but does not explicitly state when to use this tool versus alternatives. Sibling tools like learn_reputation or route_valve are not mentioned, and no when/when-not conditions are provided. The context is clear but lacks explicit exclusions.
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 have clearly distinct purposes, such as status, learning, market listing, retention, and routing. However, route_valve also returns a next action, which overlaps with the dedicated next_action tool, causing slight ambiguity.
Naming conventions are mixed: some tools start with a verb (learn_reputation, list_generation_market, route_reputation_skill, route_valve), while others are noun phrases (gateway_status, next_action, retention_plan). This lack of a consistent pattern makes it harder to predict tool names.
With 7 tools, the server is well-scoped for a reputation gateway that provides status, learning, market, routing, and retention insights. Each tool earns its place, and the count is within the ideal range.
The server covers key advisory functions like status, curriculum, market, next actions, retention, and routing, but is entirely read-only and lacks any tool to list available valves or execute actions. This leaves notable gaps for agents that need to actually interact with the reputation system.