get_artifact

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 discloses that the tool uses search-based lookup with best-effort name matching, which may return a different artifact for ambiguous names. This is key behavioral context beyond the schema.

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-loading the core purpose and caveat in the first sentence, and usage guidance in the second. Every sentence contributes meaning; no wasted 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?

Given the tool's simplicity (one required parameter, no output schema, no annotations), the description provides adequate context: purpose, behavioral nuance, and usage scenario. It could mention whether the operation is read-only, but the task does not require an exhaustive inventory.

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% with a single parameter described. The description adds value by explaining the search-based lookup behavior and providing illustrative examples (e.g., 'express'), which helps the agent understand how the parameter is used in practice.

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 it retrieves full details and capabilities for a specific AI artifact by name or slug, which is a specific verb-resource pair. It distinguishes from sibling tools like 'search' and 'find_mcps' which likely have broader scopes.

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 provides explicit usage guidance: 'Use this to understand what an artifact can do before adding it to your stack.' It also warns about ambiguous names, aiding decision-making. However, it does not explicitly list when not to use or name direct alternatives.

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