state_prompt

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It reveals the output form (a ready-made system-prompt addition) and its intended placement, but it does not state whether the tool is read-only, whether it has side effects, what data is included in the state, or how the output is generated. This is a meaningful gap for a tool with no annotation support.

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 concise: two short sentences with no filler. The core concept is front-loaded, and the usage instruction follows. The main weakness is vagueness, not structural waste or unnecessary length.

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 the tool being simple, the description leaves important context missing: what 'derselbe Zustand' refers to, how the two parameters shape the resulting prompt, and how this tool relates to siblings like state_read. Without an output schema or annotations, the description should provide more behavior and relationship context to be fully actionable.

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 50%, and the description adds no information about the parameters. It does not explain how 'partner' affects the prompt or how the 'language' option changes the output. The schema itself provides some clarity, but the description fails to compensate for the uncovered half or clarify parameter impact.

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 indicates that the tool provides the current state as a ready-made system-prompt addition and instructs the agent to read and prepend it before answering. However, 'Derselbe Zustand' has no antecedent within the description, and the tool's core action is only implied rather than stated with a clear verb. It also does not differentiate itself from siblings like state_read or state_history.

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 instruction 'Vor einer Antwort lesen und voranstellen' gives explicit when-to-use guidance: before answering, read and prepend the output. But it does not explain when not to use this tool or mention alternatives such as state_read or state_inject. The usage context is clear but incomplete.

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