Log a style learning

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

With no annotations, the description carries the behavioral transparency burden. It discloses 'append-only' (no edits/deletes), 'durable', and that entries 'accumulate and get reviewed later', providing meaningful context about the tool's non-destructive, persistent nature. It does not mention auth, return values, or edge cases, but for an append-only log this is fairly transparent.

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, front-loaded with the primary action, and includes useful examples without fluff. Every sentence earns its place, making it highly concise and well-structured.

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?

The tool is simple (2 parameters, no output schema), and the description covers the what, when, and lifecycle (accumulate, review, promote). It does not describe return values or failure cases, but for an append-only logging tool, the core context is sufficiently complete. A slightly lower score would apply if there were hidden complexities.

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 both parameters (note and tags) having descriptions. The description adds illustrative examples of note content ('decided he's done with cropped hems', 'leaning into wider trousers') but does not add technical details beyond the schema. Baseline 3 is appropriate given the schema already covers semantics.

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 opens with 'Append a durable style learning or preference shift to the Style Journal (append-only)', clearly stating the verb (append), resource (Style Journal), and scope. It distinguishes itself from style_set_directives by explaining that entries 'accumulate and get reviewed later and promoted into the mens-style skill or the directives', implying it is for logging observations rather than setting directives directly.

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?

It explicitly provides usage triggers: 'Use when Grayson states a new preference, dislike, or direction, or you notice a repeated pattern worth remembering', with concrete examples. However, it does not explicitly name sibling tools or state when not to use it, so while the guidance is clear, it stops short of fully explicit exclusions or alternatives.

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