generate_repair_prompt

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

With no annotations, the description carries the full burden and does a good job: it names the internal analysis steps (missing sources, misquoted excerpts, polarity mismatches, etc.) and the output form (structured markdown prompt). It stops short of disclosing edge-case behavior such as invalid or incomplete packet handling, but the core behavior is clear.

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 tightly packed sentences front-load the purpose and then enumerate the issue types and output format. Every phrase contributes meaning, and there is no redundant restating of the tool name.

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 a single nested-object parameter and no output schema, the description covers the input purpose, analysis scope, and output type, and directs the agent to the full contract. It would be more complete with explicit return-value details or error behavior, but what is present is largely sufficient.

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 parameter already has a baseline explanation. The description adds a useful pointer to get_schema('evidence_packet_request') and reinforces the parameter's purpose, but it does not elaborate on how each nested field is used. A 3 is appropriate since the schema carries most of the load.

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 distinct action ('Generate actionable self-correction instructions') and a specific resource ('from an evidence packet request'), then details the issue categories it inspects and the markdown prompt it produces. This clearly separates it from sibling validation/audit tools like validate_evidence or audit_claims.

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 use when repair instructions are needed from an evidence packet, but it does not explicitly state when to choose this over alternative tools, nor does it mention exclusions or prerequisites. An agent must infer the selection logic from the tool name and general context.

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