trance_signals

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

With no annotations provided, the description carries full burden and fully discloses behavioral traits: that both modes always return the defensive read, what the return values include for each mode, and the recommended action. It is thorough and transparent.

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 detailed but well-structured, starting with a clear summary ('BOTH') followed by mode-specific details. It is not overly verbose, but could be slightly more concise by breaking into separate paragraphs for readability.

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?

Despite lacking an output schema, the description comprehensively covers what is returned for each mode, including the absorption verdict. Given the tool's dual-mode complexity, it provides sufficient information for an agent to use it correctly.

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 coverage is 100%, so the baseline is 3. The description adds value by elaborating on what each mode returns and the significance of the 'lang' parameter. While the schema already describes parameters, the description provides context on usage and expected output.

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 dual purpose: detecting absorption signals (defense) and providing induction frames (offense). It specifies the required input (observation and mode) and the output (signal taxonomy or induction frames). This distinguishes it from sibling tools like 'milton_analyze' or 'meta_model_challenge'.

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 explains when to use each mode ('detect' for defense, 'induce' for offense) and provides a recommended action ('re-engage uptime'). However, it does not explicitly mention when NOT to use this tool or cite alternatives among siblings.

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