nexo_learning_apply_retroactively

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

Describes creation of deterministic followups and idempotency, plus dry_run behavior. However, lacks explicit statement about mutability or required permissions, which is partially compensated by no annotations.

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?

Two well-structured paragraphs, front-loaded with main purpose. No wasted words; every sentence adds value.

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?

Covers usage, parameters, and behavior. Without output schema, could be more explicit about return value (e.g., list of conflicts). But overall complete for practical use.

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?

All parameters are described in schema (100% coverage). Description adds extra context like followup naming convention and idempotency, going beyond schema definitions.

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?

Description clearly states the tool scans recent decisions for conflicts with a learning's prevention rule, using specific verbs 'scan' and 'surface'. It distinguishes from sibling nexo_learning_add, which invokes this automatically.

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?

Explicitly states when to use manually (longer window/different threshold) vs. automatic invocation by nexo_learning_add. Provides clear context and alternative tool.

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