re_evaluate_with_context

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

With no annotations provided, the description carries full behavioral burden. It discloses that the tool applies 'auto-tune and confidence filtering' and explains parameters like maxPromptChars (truncation control) and confidenceFilter (threshold for dropping findings). It does not mention side effects or destructive actions, but the behaviors described are accurate and useful.

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, with the first clearly stating the purpose and the second elaborating on the context. It is reasonably concise, though the second sentence is somewhat lengthy. It front-loads the key purpose, which aids agent comprehension.

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 does not explain the return value or output format, which would help the agent understand what to expect after invocation. Given the complexity (11 parameters, no output schema), additional detail on result structure would improve completeness. The description covers high-level behavior but leaves output unspecified.

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 baseline is 3. The description adds context about the feedback loop but does not provide significant additional semantic detail beyond the parameter descriptions in the schema. Each parameter is adequately described in the schema, so the description's added value is marginal.

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 purpose: re-evaluating code with developer-provided context from a multi-turn conversation. It specifies the inputs (disputed findings, accepted findings, additional context) and positions it as an 'agentic feedback loop' for adjusting evaluations, distinguishing it from simpler evaluation tools.

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 when the developer wants to provide contextual feedback from a conversation, mentioning disputedRuleIds, acceptedRuleIds, and developerContext. However, it does not explicitly state when to use this tool instead of alternatives like evaluate_code, leaving some ambiguity about the precise trigger for re-evaluation.

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