remember_code_outcome

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

The description adds context beyond annotations by mentioning 'one-shot' and the reward/punishment mechanism. Annotations already declare destructiveHint=true and idempotentHint=false, so the description does not contradict and slightly elaborates, but it omits longer-term effects or how this interacts with memory state.

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 a single, front-loaded sentence with no redundant text. It is concise, though the heavy use of biological jargon ('Mushroom Body', 'dopamine') may reduce immediate comprehensibility for some agents.

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 is adequate for a destructive mutation with no output schema, but it does not specify return values, side effects beyond 'one-shot', or how this operation fits with sibling memory tools. Annotations cover the safety profile, but the description could better explain the learning mechanism's implications.

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 minimal parameter meaning beyond the schema; it maps 'test passed' to success and 'test failed/bug' to failure, which is already captured in the outcome enum description. No extra clarity for tags or error_message.

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 states a specific verb ('Applies'), a resource ('Mushroom Body synaptic weights'), and the reward/punishment behavior based on test outcome. This clearly distinguishes it from sibling read/reset tools, though the biological metaphor ('dopamine reward', 'Mushroom Body') adds a layer of abstraction.

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?

Usage is implied: the tool records test outcomes into memory. However, there is no explicit guidance about when to use it versus alternatives like check_code_reflex or query_associative_memory, and no exclusions or conditions are stated.

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