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raise_missing_requirements

Elicit missing requirements and clarifications from the user when details are insufficient for implementation, using targeted questions and identified gaps.

Instructions

Raise Missing Requirements

Description

Elicit missing requirements and clarifications from the user when details are insufficient for implementation.

Args

  • current_request: string — Current understanding of the user’s request

  • identified_gaps: list[string] — Missing requirement gaps

  • specific_questions: list[string] — Targeted questions to clarify gaps

  • decision_areas (optional): list[string] — Fundamental decisions to confirm (e.g., database, framework, ui_type, app_type, api_style, auth, hosting)

  • options (optional): list[string] — Candidate options to present with pros/cons

  • constraints (optional): list[string] — Known constraints or non-negotiables

Returns

  • string: summary text of clarified requirements and context from the user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optionsNo
task_idYes
constraintsNo
decision_areasNo
current_requestYes
identified_gapsYes
specific_questionsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. It describes the interaction style ('elicit... from the user') and the return value, but doesn't disclose any side effects, prerequisites (e.g., needing a task_id), or whether it blocks for user input. The omission of task_id in the Args section also reduces transparency.

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?

The description is well-structured with a purpose statement, argument list, and return description. It is about the right length and each section adds value, though the markdown formatting is slightly irregular with inconsistent indentation.

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

Completeness3/5

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

The description covers the tool's purpose, parameters (mostly), and return value, but misses the required task_id and doesn't explain how the tool integrates with the broader workflow (e.g., when to use versus raise_obstacle). The lack of annotation context also leaves the tool's behavior partially unspecified.

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

Parameters2/5

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

The schema has no descriptions (0% coverage), so the description must explain all parameters. It provides helpful explanations for current_request, identified_gaps, specific_questions, decision_areas, options, and constraints, but completely omits task_id, which is required. This is a significant gap that could lead the agent to omit a required argument.

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 function: 'Elicit missing requirements and clarifications from the user when details are insufficient for implementation.' This is a specific verb+resource and distinguishes it from sibling tools like raise_obstacle or request_plan_approval, though it doesn't explicitly name alternatives.

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 provides a clear usage context: 'when details are insufficient for implementation.' This tells the agent when to invoke it, but it doesn't explicitly exclude alternatives or name sibling tools, so it lacks explicit when-not guidance.

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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