task_submit

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

With no annotations provided, the description carries the full burden and successfully discloses critical behavioral traits: continuous execution (24/365), automatic retry logic, and completion-based termination. It could be strengthened by mentioning failure modes (e.g., max retry limits) or return values, but the execution model disclosure is substantial.

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?

Extremely efficient structure: one sentence for purpose/behavior, a header '投入する4項目:', then four bullet-style parameter definitions. Every line earns its place. The critical behavioral information (24/365, retry) is front-loaded before parameter details.

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 4-parameter flat schema with no output schema, the description adequately covers operational context. It explains what happens after invocation (AI takes over execution). Minor gap: doesn't describe the return value (likely a task ID) or how to reference the task later, though sibling tools suggest this functionality exists.

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 100%, establishing a baseline of 3. The description adds significant value by providing a concrete, syntax-rich example for the 'done' parameter: '例: "npx tsc通過 + vitest全パス"'. This example clarifies expected machine-verifiable formats beyond the schema's abstract description.

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 opens with '自律タスクを投入する' (submit autonomous tasks) and immediately clarifies the unique execution model: 'AIが24/365で自動実行し、完了条件を満たすまでリトライする' (AI executes automatically 24/365, retrying until completion conditions are met). This specific verb+resource+behavioral scope clearly distinguishes it from siblings like task_status (query) or memory_save (storage).

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 24/365 auto-execution and retry behavior implicitly signals when to use this (for persistent background tasks) versus one-shot operations. While it doesn't explicitly name alternatives like 'use task_status to monitor progress,' the operational model is distinct enough to guide selection. Lacks explicit 'when not to use' guidance.

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