Get focus heatmap (hour × weekday grid)

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

With no annotations, the description clearly explains the output structure (168-cell grid, indexing order, weekday starting Sunday) and filter behavior, but does not mention potential side effects, auth needs, or rate limits. It is transparent about data shape and ordering.

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?

Three sentences are efficient: first states what it returns, second explains value, third adds indexing detail and filter hints. Every sentence earns its place; no redundancy.

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 5 optional parameters, no output schema, and no annotations, the description covers the grid structure, ordering, filter usage, and purpose. It lacks return value details but the grid format is explained sufficiently for an agent.

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%, providing baseline 3. The description adds meaningful context: explains period format, mentions 'canonical name' for app, 'exact match' for project, and details device options including 'current', UUID, or platform. This goes beyond raw 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 returns a 'dense 168-cell grid (7 weekdays × 24 hours) of active foreground seconds', with optional filters. It distinguishes itself from sibling tools by focusing on a heatmap that reveals patterns beyond marginal distributions.

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 use for discovering work patterns not shown by hour-of-day/weekday distributions, but does not explicitly state when to use this tool over siblings like get_app_breakdown or get_category_breakdown, nor does it provide exclusions or alternatives.

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