write_artifact

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

With no annotations, the description fully discloses key behaviors: in-place update (URL never changes), versioning with artifact_history and revert, auto-detection of React/JSX, and no-op behavior for identical content (unchanged: true). This exceeds expectations for a write operation.

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 well-structured: an opening tagline, followed by behavioral details, and ended with a concrete usage loop. Every sentence adds value, and the content is organized logically without redundancy.

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?

Given the complexity (5 parameters, no annotations) and the existence of an output schema, the description is complete enough. It covers prerequisites, limitations, edge cases, and the typical workflow, leaving no ambiguity 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?

The schema covers 100% of parameters with detailed descriptions, so the baseline is 3. While the tool description reinforces some parameter behaviors (e.g., content replacement, message in history), it adds no new parameter-specific meaning beyond the schema.

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 a clear, specific verb and resource: 'Write a new iteration of a *mutable* artifact' and uses the git commit metaphor to clarify the versioning nature. It also distinguishes from siblings like read_artifact and artifact_history by focusing on mutation and versioning.

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 explicitly states when this tool is applicable: only for artifacts saved with mutable=true, and it warns that immutable artifacts return an error with guidance to re-create as mutable. It also provides a typical usage loop with read_artifact, making the intended workflow clear.

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