get_editing_knowledge

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

No annotations are provided, so the description carries full burden. It discloses that results include 'concrete numbers and mappings to tool parameters', which is helpful. However, it does not explicitly state the tool is read-only or discuss any side effects, rate limits, or data size.

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 short sentences, front-loaded with the core purpose and including all needed context without extraneous words. Every part adds value.

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 has one optional parameter with an enum, no output schema, and no annotations, the description adequately covers what the tool does and what the parameter controls. It could mention that it's a read operation, but the content is complete enough for an AI agent to invoke correctly.

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%, so baseline is 3. The description adds that omitting topic lists available topics, which partially echoes the schema description. It also adds context about returning numbers and mappings, but does not significantly enhance understanding 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 clearly states the tool reads editorial knowledge, explicitly listing the topics (color looks, beat-cutting, etc.) and contrasting it with 'not just operating the app'. This distinguishes it from sibling tools that perform actions like assembling, color matching, or cutting.

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 implies the tool is for editorial guidance (e.g., 'for editing well') and mentions that omitting topic lists available subjects. It does not explicitly exclude use cases or name alternatives, but the contrast with 'operating the app' hints at when not to use it.

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