update_reputation

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It transparently states the direction of state changes (success increases mu, decreases sigma; failure opposite) and the scaling effect of evidence class. It does not discuss permissions or error cases, but the core behavior is well described.

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 concise sentences, front-loaded with the action and immediately followed by the key behavioral details. Every clause 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 mutation tool with no output schema, the description covers purpose, behavior, and a key parameter relationship. It lacks explicit guidance on choosing this tool over sibling reputation tools and omits permission requirements, but given the schema's completeness and the simple nature of the update, it is adequately contextualized.

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 describes all 5 parameters (100% coverage). The description adds useful semantic information by explaining how 'success' affects mu/sigma and how 'evidenceClass' influences magnitude—details not present in the schema. It does not elaborate on scope/principalId, but overall it enriches parameter understanding.

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 phrase ('Update an agent's reputation') and clearly indicates the context and effect ('after a task result'). It also distinguishes itself from sibling tools by naming the internal mu/sigma mechanics and evidence class scaling, which separates it from tools like vouch_reputation or apply_reputation_downgrade.

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 gives a clear usage context ('after a task result') and explains the expected effect based on success/failure. However, it does not explicitly mention alternative tools or state when not to use this tool, so it stops short of full comparative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.