tune_policy_rule

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

With no annotations, the description must fully disclose behavior. It mentions 'Contextual Bandit' but does not clarify whether the tool modifies state, requires prior data, or simply recommends an action. No mention of side effects or permissions.

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?

Single 16-word sentence that is front-loaded with the algorithm name and purpose. Every word is informative with no redundancy.

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?

Given 3 required parameters with no descriptions, no output schema, and many sibling tools, the description is insufficient. It omits return value, prerequisites (e.g., existence of policy rule), and how it relates to tools like 'generate_policy_from_observations'.

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 0%, so the description must explain parameters. It only says 'based on context' without mapping to serverType, agentTier, or ruleCategory. Parameter meaning is entirely left to inference from names.

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 uses Contextual Bandit (LinUCB) to select from three actions (enforce/relax/skip) based on context. It distinguishes itself from sibling tools like 'adapt_threshold' and 'suggest_policy_improvements' by specifying the algorithm and action space.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies policy rule tuning but does not state prerequisites, when it is appropriate, or when other tools like 'ab_test_policy' should be used instead.

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