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

Adds substantial behavior beyond the annotations: allocation is validated against pool capacity before applying and a refused allocation is restored, the call is asynchronous and returns a job_id to poll, there are per-module and per-project mutual-exclusion constraints, and maintenance windows produce a specific retryable refusal. This is exactly the retry/idempotency/auth context an agent needs.

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?

Front-loads what the tool does, then follows with async, concurrency, and retry semantics in order of operational importance. It is dense and slightly repetitive around get_job_status usage, but almost every sentence carries distinct actionable information.

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 3-parameter mutation with no output schema and full schema coverage, the description covers the async flow, refusals, and concurrency rules an agent must handle. It could still note whether resources can be lowered or what the job result reports, but nothing essential for invoking it correctly is missing.

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 description coverage is 100%, so module_id, cpu_millicores, and memory_mb are already documented in the schema. The description adds the capacity-check constraint on the allocation but no format, range, or unit nuance beyond what the schema provides, so the baseline of 3 applies.

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 concrete verb (set) and resource (module's CPU and memory) plus the side effect (rebuild so pods take them), which is a specific operation an agent can recognize. It does not explicitly contrast itself with the near-siblings scale_module, update_module, or redeploy_module, so sibling differentiation is left to inference.

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?

Gives explicit operational context: results are asynchronous and must be polled via get_job_status, only one operation per module/project at a time, and how to recover from a refusal (wait for the named running job, then retry) or a maintenance-window refusal. It never states when to prefer this tool over scale_module/update_module, so the alternative-selection guidance is missing.

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