apply_plan_adjustment

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

No annotations provided, so description must carry burden. It indicates the tool returns a plan JSON without persisting it, implying no side effects. However, no details on authentication, rate limits, or error conditions are given.

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?

Two concise sentences with no extraneous information. The first sentence covers the core function, the second adds important context about decision process.

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?

With no output schema and no annotations, the description lacks detail on the returned JSON structure and the effects of each adjustment type. It adequately identifies inputs but fails to describe tool behavior comprehensively.

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 description coverage is 0%, so baseline is 4. The description lists the adjustment types, which adds value beyond the schema's enum. However, it does not explain the other fields (reason, deltas) or how adjustments modify the plan, thus only partially compensates.

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?

Clearly states the tool applies adjustments to a plan template and returns the adjusted plan JSON. Mentions the four adjustment types. Distinguishes from siblings like suggest_session_modification or get_template_plan by focusing on plan-level adjustments.

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?

No explicit guidance on when to use this tool versus alternatives. The note about persistence and user veto provides some context but fails to clarify scenarios or prerequisites.

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