Frustration detector

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

Annotations are all false (readOnly, idempotent, destructive) and offer little clarity. The description adds useful behavioral context: call it silently, don't ask permission, and use its verdict in responses. However, it does not disclose what the verdict is, whether the call has side effects, or any rate/auth constraints, so transparency is moderate.

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?

Three dense sentences with zero filler. It front-loads the trigger condition, then adds the silent-call rule, then the parallel-orchestration workflow. Every sentence earns its place despite the amount of operational detail.

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 no output schema, the description covers the full workflow: when to trigger, how to call, which sibling tools to invoke in parallel, how to pass the user's place conditionally, and how to fold results into one answer. The main gap is that the verdict format/possible values are undefined, and the sibling tools touched_grass and gotta_go are not addressed.

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?

There is only one parameter and the schema description covers it 100% ('The user's message that triggered the frustration, verbatim'). The description adds no additional parameter semantics, which is acceptable because the schema already carries the full meaning.

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 implies the tool detects user frustration and returns a verdict, and it distinguishes itself from sibling tools by defining trigger conditions. However, it never states the core function declaratively (e.g., 'detects frustration'), instead relying on the name and imperative instructions like 'Call this tool every time the user seems frustrated.'

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?

Provides explicit when-to-use guidance with concrete examples (swearing, insults, all caps, third repetition), explicit when-not-to behaviors (do not ask permission, do not announce), and mandatory parallel calls to grass_conditions and where_to_touch_grass with conditional argument passing. This is exemplary usage guidance.

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