backtracking

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

With no annotations, the description carries full burden. It explains the tool rewinds to the last stable state, explores alternatives, and produces a patched plan. It does not mention side effects or permissions, but for a prompt generation tool, this is adequate.

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 well-structured docstring with Args and Returns sections. It is concise, using minimal but complete sentences. Minor fluff could be trimmed, but it is effective.

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 lack of annotations, the description covers the tool's purpose, inputs, and output sufficiently. It does not mention idempotency or error handling, but for a scaffold generator, this is reasonable.

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 does so by explaining each parameter: objective as overall goal, failed_step as the step that failed, trace as optional reasoning trace, constraints as guardrails. This adds meaningful context beyond the 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 it produces a recursive backtracking scaffold for error correction, with a specific verb and resource. It is distinct from sibling tools like 'analyze_task_complexity' or 'design_context_architecture' which focus on analysis and design, not error correction.

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 an error or failure occurs, with parameters for the failed step and objective. However, it does not explicitly state when not to use or suggest alternative tools, which would improve guidance.

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