Recall

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions creating a 'validation event' and adjusting confidence, which hints at mutation effects, but doesn't specify permissions required, whether changes are reversible, rate limits, or error handling. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 well-structured with a purpose statement, parameter explanations, and return value note. It's appropriately sized—each sentence adds value. Minor improvement could be front-loading the return info, but overall it's efficient with zero waste.

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 the tool's moderate complexity (mutation with 4 parameters), no annotations, but with an output schema (implied by 'Returns' note), the description is fairly complete. It covers purpose, parameters, and return values, though behavioral aspects like side effects or error cases could be more explicit. The output schema reduces the need to detail return formats.

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 compensate fully. It provides clear semantics for all four parameters: memory_id ('ID of the memory that was applied'), success ('Whether the application was successful'), error_msg ('Optional error message if failed'), and session_id ('Optional session identifier'). This adds substantial value beyond the bare schema.

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: 'Record the outcome of a memory application and adjust confidence.' It specifies the verb ('record'), resource ('outcome of a memory application'), and effect ('adjust confidence'). However, it doesn't explicitly differentiate this from sibling tools like memory_validate_tool or validation_history_tool, which appear related to validation events.

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 context ('Records whether applying a memory succeeded or failed') but doesn't provide explicit guidance on when to use this tool versus alternatives like memory_validate_tool or validation_history_tool. No exclusions or prerequisites are mentioned, leaving the agent to infer usage from the purpose alone.

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