update_reputation

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

With no annotations, the description must fully disclose behavior. It explains the effects on mu and sigma based on success/failure and evidence class. However, it does not mention side effects, authorization requirements, reversibility, or rate limits, which are important for safe invocation.

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 sentences, front-loading the purpose and effect, with no unnecessary words. Every sentence adds value.

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 description explains the core behavior adequately but omits return value information. Given the tool has no output schema, the agent needs to know what the response looks like. It also misses prerequisites or post-conditions.

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%, so the baseline is 3. The description adds implicit context for evidenceClass (larger effect), but does not elaborate on the specific parameters beyond what the schema already provides.

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 verb 'Update' and the resource 'agent's reputation', and specifies the context ('after a task result') with behavioral effects (mu and sigma changes). However, it does not explicitly differentiate from the sibling tool 'apply_reputation_downgrade', which could be a close alternative.

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 usage after a task result, but provides no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives like 'apply_reputation_downgrade' or conditions that would make this tool inappropriate.

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