train_bootstrap

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

With no annotations, the description carries the full burden. It discloses that the tool is dockerless, idempotent, takes ~10 min fresh, and that pod's /workspace persists restarts. This provides good behavioral transparency without contradictions.

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 sentences, no wasted words. The first sentence states the core action, and the second adds timing and context. Front-loaded and efficient.

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 no output schema and two optional params, the description covers purpose, usage scenario, behavioral traits, and prerequisite relationship with 'train_start'. It is complete for a setup tool.

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 schema describes 'pod_id' and 'target', but the description adds context: 'target' choices (local/pod) are clarified by mentioning 'on this machine or a pod' and linking 'pod' to 'train_start'. This adds meaning beyond the schema for the 'target' parameter, which had no explicit 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 clearly states the tool sets up the native trainer by cloning the repo, creating a venv, and installing requirements. It distinguishes from siblings by focusing on bootstrapping, a prerequisite for training, which is distinct from other training or utility tools.

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 explains that this tool is needed before 'train_start' on a fresh pod and mentions idempotency and one-time setup. It doesn't explicitly list when not to use or alternatives, but the context is clear enough.

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