Ein sofort lauffähiger Beispiel-Payload für solve_submit. kind='simple' (1 Woche, 3 MA, 2 Schichten), kind='wishes' (Wünsche, Social Points, Wunschkosten) oder kind='rules' (ArbZG-Planungsregeln: 11 h Ruhe hart + max. 5 Folgetage — zeigt, wie Regeln den Plan formen; Param-Namen sind exakt, falsche werden still ignoriert).
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | simple |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that incorrect parameter names are silently ignored, which is a useful behavioral trait. However, it does not mention whether the tool is read-only, idempotent, or has side effects, leaving some gaps.
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 single sentence that is front-loaded with the core purpose ('sofort lauffähiger Beispiel-Payload für solve_submit') and then efficiently elaborates on the three kinds. No redundant information, every part earns its place.
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 tool with one optional parameter and an output schema, the description covers the parameter fully and mentions a behavioral detail. It does not explicitly state that the output is a valid payload for solve_submit, but this is implied by the purpose. Sibling tools are diverse and not relevant to completeness.
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 input schema has only one parameter (kind) with a default but no description or enum, resulting in 0% schema coverage. The description fully compensates by explaining the three possible values (simple, wishes, rules) and their meanings, adding critical semantic 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 the tool provides an immediately runnable example payload for solve_submit, with three distinct kinds (simple, wishes, rules) each explained. This distinguishes it from sibling tools like solve_submit, solve_status, etc., which have different purposes.
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 the tool is used to obtain example payloads for solve_submit, but it does not explicitly state when to use it versus alternatives (e.g., before calling solve_submit to test inputs). No when-not or exclusion guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool has a clearly distinct purpose: account_balance for token info, example_payload for generating example requests, service_info for version details, and the solve_* trio (submit, status, result) covering the full lifecycle without overlap.
All names use lowercase underscores, and the core workflow tools consistently start with 'solve_'. The administrative tools (account_balance, example_payload, service_info) follow a noun_noun pattern, which is slightly different but still readable and predictable.
With 6 tools, the server is well-scoped: three tools for the core planning workflow, plus essential support tools for tokens, examples, and version info. No tool feels redundant or missing.
The solve lifecycle is fully covered (submit, status, result). The addition of example payload and account balance addresses common needs. Minor gaps like job cancellation or listing are absent but not critical for the main use case.