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ouroboros_pm_interview

Gathers product requirements via structured PM interviews; resume with session ID, or generate a PM seed from completed interviews.

Instructions

PM interview for product requirements gathering. Start with initial_context, continue with session_id + answer, or generate PM seed with action='generate'. In plugin mode, returns a delegation receipt (status=delegated_to_subagent) and the PM interview executes in an OpenCode Task pane — the real session_id is returned there.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory for PM document output. Defaults to current working directory. Brownfield context is loaded from DB (is_default=true).
actionNoAction to perform. Auto-detected from parameter presence when omitted: initial_context → 'start', session_id + answer → 'resume'. Use 'generate' explicitly to produce PM seed from completed interview.
answerNoPM's response to the current interview question
session_idNoSession ID to resume an existing PM interview
last_questionNoThe question text from the previous child session's response. In plugin mode each dispatch creates a new child session whose questions are not automatically persisted server-side. Pass the child's last question here when submitting an answer so the PM interview transcript preserves the real question text instead of a placeholder.
selected_reposNoList of repository paths selected for brownfield context (2-step start: returned by step 1, sent back in step 2). All repos are assigned role=main. When provided with initial_context, starts the interview with the selected brownfield repos.
initial_contextNoInitial product description to start a new PM interview
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does a good job: it explains plugin-mode execution, the delegation receipt (status=delegated_to_subagent), where the real session_id is returned, and that action can be auto-detected. It also mentions that brownfield context is loaded from DB. These are meaningful behavioral details beyond the schema, though it does not cover every edge case like error handling or persistence side effects.

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 packs a wealth of information into two dense sentences. It front-loads the purpose and then logically explains the three usage modes with clear parameter references. Every clause serves a purpose; the plugin-mode caveat is included succinctly. No filler or redundant restatement of the schema.

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

Completeness4/5

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

For a tool with 7 parameters, no output schema, and no annotations, the description plus rich parameter descriptions provide a solid understanding. The description covers the core interaction patterns and the important plugin-mode exception. It lacks explicit details on response formats (beyond the delegation receipt) and failure conditions, but given the complexity, it is reasonably complete for an agent to use correctly.

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

Parameters4/5

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

Schema description coverage is 100% (all 7 parameters are documented), so the baseline is 3. The description adds value by explaining the workflow: initial_context starts, session_id+answer resumes, and action='generate' produces a PM seed. This explicitly ties parameters to usage modes and clarifies auto-detection, going beyond the individual parameter descriptions.

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 opens with 'PM interview for product requirements gathering,' which clearly states a specific verb (interview) and resource (product requirements). It distinguishes this tool from siblings like ouroboros_interview by focusing on PM/product requirements scope and its multi-step workflow. The description also enumerates distinct usage modes, leaving no ambiguity about what the tool accomplishes.

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 gives explicit instructions on how to interact: 'Start with initial_context, continue with session_id + answer, or generate PM seed with action='generate'.' This is clear when-to-use guidance for each parameter combination. It also notes the plugin-mode delegation behavior, which is an important operational context. However, it does not explicitly compare against alternative tools or state when not to use this tool, so it falls short of a 5.

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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