parameter_sweep

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

Annotations declare a non-read-only, non-idempotent, non-destructive mutation, and the description adds substantial context beyond that: source preservation, per-run time limits, per-point status, a durable partial summary, cancellation behavior that preserves the checkpoint, and hash-checked resume. It omits where outputs land and any authorization or concurrency constraints, keeping it short of a 5.

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 core action and output format are front-loaded in the first sentence, with operational mechanics following in short clauses. Density is high and nearly every clause carries information, though the run-limit and sampling rules could be grouped more cleanly.

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?

An output schema exists, so return values need not be described, and the behavioral section is strong. However, for a 9-parameter mutation tool with zero schema description coverage, four core parameters (path, component, parameter, variable) remain opaque, leaving the definition incomplete for correct invocation.

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 0% across 9 parameters, so the description must carry the burden, and it only partially does. It clarifies fail_fast ('stops after a failed point'), resume_from ('retries unfinished points after checking source and data hashes'), the values count (1..20), the timeout bound (1..30 seconds), and ties frequency_hz to sampling ('must exist as an actual sample'). It leaves path, component, parameter, and variable completely unexplained.

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 names a specific verb ('Simulate') and resource ('independent parameter variants'), states the cardinality bounds (1..20) and output shape (JSON/CSV comparison), so the agent knows exactly what the tool does. It does not, however, contrast itself with siblings like update_parameters, run_schematic, or compare_results, which appear closely related.

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?

There is no explicit statement of when to choose this over update_parameters or run_schematic, and no when-not guidance. Some usage is implied through the fail_fast and resume_from mechanics, but the agent must infer the decision context entirely.

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