testgen-flow-question-generation

testgen-flow-question-generation is a command for coding agents from griddynamics/rosetta. It costs 15 tokens per session (2,777 once invoked), scanned A, original, Apache-2.0.

Phase 3 Question Generation of testgen-flow.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/griddynamics/rosetta/testgen-flow-question-generation
Clone the repo
git clone --depth 1 https://github.com/griddynamics/rosetta

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for testgen-flow-question-generation

README.md
[![agentmods](https://agentmods.dev/badge/commands/griddynamics/rosetta/testgen-flow-question-generation.svg)](https://agentmods.dev/commands/griddynamics/rosetta/testgen-flow-question-generation)
Your own site
<a href="https://agentmods.dev/commands/griddynamics/rosetta/testgen-flow-question-generation"><img src="https://agentmods.dev/badge/commands/griddynamics/rosetta/testgen-flow-question-generation.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,777 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00015 $0.02777
Opus 5 $0.00008 $0.01388
Sonnet 5 $0.00003 $0.00555
Haiku 4.5 $0.00002 $0.00278

Measured today against content hash be2949680957, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

testgen-flow-question-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/core-copilot-light/commands/testgen-flow-question-generation.md · 277 lines

How it starts

The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<testgen_flow_question_generation>

<description_and_purpose> Generate specific, actionable clarification questions based on analysis findings, collect user answers, and validate completeness. This is the primary HITL gate — user input is required before proceeding to requirements generation. </description_and_purpose>

<workflow_context>

  • Phase 3 of 7 in testgen-flow
  • Input: analysis.md from Phase 2
  • Output: questions.md (for user), answers.md (structured user responses by AI based on answers in questions.md)
  • Recommended skills: questioning
  • Prerequisite: Phase 0, 1, 2 complete
  • HITL GATE: MUST WAIT for user to provide answers. Explicit approval required. Do not assume user approved — if user sends questions or suggestions, that is reviewing, not approval. </workflow_context>

<phase_steps>

  1. Generate clarification questions (loads analysis + formats by issue type) → step 3.1
  2. Prioritize and create questions document → step 3.2
  3. Validate user answers → step 3.3
  4. Create answers document → step 3.4
  5. Update state file → step 3.5 </phase_steps>

<generate_questions step="3.1">

  1. Read plans/testgen-{TICKET-KEY}/analysis.md
  2. USE SKILL questioning to formulate targeted clarification questions from analysis findings
  3. For each contradiction: present both conflicting source quotes, ask which is correct, offer options (a/b/c/other)
  4. For each gap: explain what's missing and why needed, provide examples or options
  5. For each ambiguity: quote vague statement, ask for specific definition or measurement
  6. Related issues can be combined: e.g., Q5: G3, G4, A2 - User Permissions Model
  7. Quality rules: specific, actionable, includes context, offers options — NOT vague or open-ended

<question_format_for_contradictions>

### Q[N]: [Issue ID] - [Brief Title]
**Issue Type**: Contradiction
**Context**: 
- Ticket states: "[quote]"
- Wiki states: "[quote]"

**Question**: Which statement is correct, or should we use a different approach?
**Options**:
  a) Use the ticket version: [specific value]
  b) Use the Wiki version: [specific value]
  c) Use alternative: [specify]
  d) Other (please specify)

**Your Answer**: 
[Leave blank for user]

</question_format_for_contradictions> <question_format_for_gaps>

### Q[N]: [Issue ID] - [Brief Title]
**Issue Type**: Gap (Functional/Non-Functional/Data/Business Logic/Dependency)
**Context**: [Where this is needed in implementation]

**Question**: [Specific question about missing information]
**Examples/Options** (if applicable):
  - Option 1: [example]
  - Option 2: [example]
  - Other: [allow free text]

**Your Answer**: 
[Leave blank for user]

</question_format_for_gaps> <question_format_for_ambiguities>

### Q[N]: [Issue ID] - [Brief Title]
**Issue Type**: Ambiguity
**Vague Statement**: "[quote from source]"

**Question**: Can you clarify what "[vague term]" means specifically?
**Need to Know**:
  - [Specific aspect 1]
  - [Specific aspect 2]

**Your Answer**: 
[Leave blank for user]

</question_format_for_ambiguities>

<good_questions>

  • "Should the authentication use OAuth 2.0, SAML, or Basic Auth?"
  • "What is the maximum response time requirement (in milliseconds)?"
  • "Should users be able to delete records permanently, or soft-delete only?" </good_questions>

<poor_questions>

  • "How should authentication work?" (too broad)
  • "Should it be fast?" (vague)
  • "Tell me about the feature." (not specific) </poor_questions> </generate_questions>

<create_questions_document step="3.2">

  1. Group questions by priority: P0 (Critical, MUST answer), P1 (High), P2 (Medium), P3 (Low)
  2. Create plans/testgen-{TICKET-KEY}/questions.md using the questions.md template defined in <questions_template> below
  3. Update state to "AWAITING USER INPUT"
  4. Notify the user and direct them to give answers by editing the file: give the questions.md path and ask them to fill the [Leave blank for user] fields there. A short chat summary of the questions is fine for orientation, but the authoritative answers are collected in questions.md — do NOT run a chat Q&A in its place, and do NOT accept chat replies as a substitute for the file (validate_answers, step 3.3, reads the file, not the chat). This keeps every question visible and answerable to the user, instead of only the ones the agent chose to surface in chat.
  5. PAUSE — WAIT FOR USER INPUT

Read the full file on GitHub · 277 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 277 lines · 15 tokens per session scan A be2949680957

Subscribe to this mod's changes

testgen-flow-question-generation is a command published in the GitHub repository griddynamics/rosetta (342 stars, last pushed today), licensed Apache-2.0. It adds 15 tokens to every session and 2,777 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.