storyline_edit_strategy

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions 'AI-driven edit' and shows it can remove line items, but it does not clarify whether the edit is destructive, reversible, or requires confirmation, nor whether it modifies the strategy in place or returns a preview. This lack of safety/effect context is a notable gap for a mutating tool.

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 extremely concise: one core sentence plus two illustrative examples. Every element earns its place, and the front-loaded verb 'Apply' immediately conveys action. 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?

For a mutation tool with no output schema and no annotations, the description should clarify what the result of the edit is (e.g., updated strategy object, success message) and what the edit scope covers. The examples and schema partially cover scope, but the lack of return value/confirmation info leaves the description incomplete for an agent to anticipate the tool's full behavior.

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 input schema provides 100% coverage with clear descriptions for all three parameters (storylineId, instruction, brandId). The description adds little beyond the schema, only contextualizing the instruction parameter via examples. Baseline 3 is appropriate since the schema already does the heavy lifting.

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's function: applying an AI-driven edit to the current strategy using natural-language instruction. The verb 'Apply' with 'edit' and the resource 'strategy' is specific, and the examples ('Add a LinkedIn video post', 'Remove influencer outreach') make the purpose tangible. It is distinguishable from siblings like storyline_update or storyline_generate_strategy by emphasizing AI-driven, instruction-based editing.

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 usage (when you have a natural-language instruction to modify the strategy) but does not explicitly state when to use this tool versus alternatives like storyline_add_line_item or storyline_update_line_item. The examples suggest typical edit scenarios but provide no exclusions or guidance on choosing this over more targeted line-item tools.

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