agent_prompt_compiler

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

No annotations are provided, so the description must carry the full behavioral burden. It mentions output characteristics ('hallucination-resistant XML system prompts with guardrails') but does not disclose processing behavior, error handling, determinism, or side effects.

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?

A single, front-loaded sentence with no wasted words. It clearly states the transformation and the output characteristics.

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?

For a simple one-parameter tool with no output schema or annotations, the description gives enough to understand the core transformation and output type. However, it omits usage guidance, input expectations, and behavioral details that would help an agent invoke it reliably.

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?

The single parameter has 0% schema description coverage, and the description only repeats its name ('raw instructions') without adding format, length, content expectations, or examples. It does not compensate for the missing schema documentation.

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?

States a specific verb ('Compiles') and resource ('raw instructions') with a clear output ('structured, hallucination-resistant XML system prompts with guardrails'). It is distinct from siblings like json_repair or hallucination_auditor, though it never explicitly compares itself to them.

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 no explicit guidance on when to use this tool versus alternatives, nor any when-not conditions or prerequisites. The purpose implies it transforms raw instructions into system prompts, but usage context is left to inference.

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