validate_snapshot

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 transparently discloses what it checks (required fields, tool-entry shape) and the return format (valid=true or list of issues). It does not mention side effects, but as a validation tool it inherently is non-mutating. It also does not detail edge-case behavior, but overall it is quite transparent.

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 two sentences long, front-loaded with the action and target, and every sentence provides value. No redundant or unnecessary words.

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 validation tool with a single parameter and no output schema, the description covers the purpose, validation criteria, and return format. It is sufficiently complete for an agent to understand the tool's behavior and what to expect.

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%, and the schema already describes the snapshot parameter as a JSON-decoded object from expectSnapshot(). The tool description adds no extra parameter-specific details beyond what the schema provides, so the baseline of 3 is appropriate.

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 validates a snapshot object against the agentsnap Trace schema, specifying exactly what it verifies (required fields and tool-entry shape). It distinguishes itself from sibling tools normalize_trace and diff_traces, which serve 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?

It provides clear context for when to use the tool: to sanity-check a snapshot against the schema. However, it does not explicitly name alternatives or specify when not to use it, though the sibling tool names imply other operations like normalization and diffing.

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