optimise_knowledge_stacks

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

With no annotations, the description carries the full disclosure burden. It usefully clarifies that the tool only *suggests* (rather than applies) changes, and that suggestions derive from live Studio data, which counters the imperative name "optimise_*". However it says nothing about permissions, scope of the scan, latency, or side effects.

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?

A single eight-word sentence with no filler, front-loading the verb and outcome. It is appropriately sized, though the extreme brevity leaves little room to earn its place beyond restating the core action.

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?

An output schema exists, so return values need not be explained, and a zero-parameter tool has no argument semantics to cover. Still missing is the scope of the analysis (all stacks vs. a workspace) and what "live Studio data" concretely includes, which limits how confidently an agent can predict the result.

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 has zero parameters, so there is nothing for the description to disambiguate. The baseline of 4 applies; the description does not contradict or confuse the empty parameter set.

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 names a specific verb ("Suggest") and resource ("Knowledge Stack optimisations") plus the data source ("live Studio data"), which distinguishes it from sibling list_knowledge_stacks and analyse_* tools. It is clear what the tool does, though it never explicitly contrasts itself with any sibling.

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?

There is no when-to-use or when-not-to-use guidance, and no alternatives are named. An agent must infer that this is the tool to call when it wants improvement suggestions for knowledge stacks; nothing states prerequisites or what to call first (e.g. list_knowledge_stacks).

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