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read_planning

Retrieve all planning slots for a specified year, including time slots and user assignments, with optional filtering by activity.

Instructions

Read all planning slots for a given year via the bot API.

Returns actual time slot data (start_time, end_time, day of year, user assignments) and group controls (recursive assignment groups).

Args: year: Year to read (e.g. 2026). Returns all slots for that year. id_activity: Optional — filter to a specific activity. 0 = all activities.

Returns: JSON string — a readable report with: - Per-activity summary: activity_id, group_title, date_range, active_weekdays, slots: [{day_of_year, user_id, start_time, end_time}] - If id_activity is 0, all activities are included. - If id_activity is set, only that activity's slots are returned.

Workflow: 1. Call list_activities to get activity IDs 2. Call read_planning(year=2026) to get all slots 3. Filter by activity or user as needed

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
id_activityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It comprehensively describes the return format (JSON with per-activity summary, slots, etc.) and parameter effects. It does not mention side effects, but as a read-only tool this is acceptable. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and concise. It starts with the core purpose, then details the return format, and ends with a workflow. Every sentence adds value without redundancy. Appropriate length for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (not shown but indicated), the description aligns well by explaining the return structure. All necessary information is covered: parameters, return format, and usage workflow. No gaps are evident.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains both parameters in detail: year (example 2026, returns all slots for that year) and id_activity (optional, 0 means all activities). This adds significant meaning beyond the input schema, which only provides types and defaults. Schema coverage is 0%, but the description fully compensates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Read all planning slots for a given year via the bot API'. It specifies the resource (planning slots), the verb (read), and the context (year). This distinguishes it from sibling tools which handle assignments, nodes, or mindmaps.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a 'Workflow' section that advises calling list_activities first and then filtering, providing practical guidance. It explains the optional id_activity parameter and its behavior. However, it does not explicitly state when not to use the tool or mention alternatives.

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

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