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propose_initialization_options

Provides a structured menu of schema source options—analyze tasks, parse taxonomy, or use presets—to guide onboarding discussion.

Instructions

Return structured onboarding choices for the user/model to discuss.

Read-only: does not write config, schema, or task data.

Call after get_initialization_status confirms onboarding is required. Use this to present a structured schema-source menu rather than guessing a path. For the next step, choose one of: analyze_existing_tasks_for_schema — infer schema from tasks analyze_taxonomy_file — parse a taxonomy Markdown file list_preset_schemas / use_preset_schema — bundled presets generate_initial_schema_preview — combine taxonomy + tasks

project_dir: optional path scoping task analysis to a project subdirectory. Pass empty string (default) to analyse all tasks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_dirNo

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 fully documents behavior: declares read-only nature twice, notes that no config/schema/task data is written, and describes the parameter's effect. It does not mention rate limits or idempotency, but given the read-only, side-effect-free nature, this is sufficient. 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.

Conciseness4/5

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

At ~150 words, the description is longer than ideal but well-structured. It opens with the core purpose, immediately states read-only nature, then provides usage order and alternatives, finally adding parameter detail. Every sentence adds value, though some repetition of 'read-only' occurs.

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 the output schema exists (so return format is documented separately), and the tool has 33 siblings, the description covers the critical context: when to call it, what it returns (menu), and what to do next. No gaps remain for an agent to misuse the tool.

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 single parameter 'project_dir' has 0% schema description coverage, but the description adds rich semantics: 'optional path scoping task analysis to a project subdirectory. Pass empty string (default) to analyse all tasks.' This clarifies behavior far beyond the bare schema.

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: returning structured onboarding choices. It specifies what the tool does not do (read-only, no config writing) and distinguishes from sibling tools by framing the output as a menu for subsequent step selection. The verb 'propose' plus structured object is specific and unambiguous.

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

Usage Guidelines5/5

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

Explicit guidance is provided: 'Call after get_initialization_status confirms onboarding is required.' It also lists concrete next steps (analyze_existing_tasks_for_schema, etc.) and tells the agent to choose one. This is clear when-to-use and what-to-do-next advice.

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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