Automated summary
Runs a structured requirements-discovery interview before implementation: creates a Trellis task, seeds the PRD, and converges on an MVP scope by asking one question at a time.
Strengths
- Enforces one question per message, each with a recommended answer, instead of dumping a questionnaire on the user.
- Captures ideas immediately by creating the task directory and filling a structured prd.md (goal, assumptions, acceptance criteria, definition of done, out of scope).
- Prefers inspecting the repo and doing technical research over asking the user to invent options.
- Forces a diverge-then-converge pass with an explicit out-of-scope list to lock the MVP.
Limitations
- Tightly coupled to the Trellis layout (.trellis/scripts/task.py and the /trellis:start command), so it won't run as-is outside a Trellis project.
- Stops at the PRD — it does no implementation or verification of the result.
- The relentless interviewing can be overkill for small changes, and the provided SKILL.md is cut off mid-section.
Use it when a new feature or vague request needs proper scoping before any code is written.
Skip it for a small, already well-specified fix or when an approved PRD exists and only implementation remains.
Security analysis
CautionThe skill primarily provides guidance for requirements discovery and only uses bash to run a local script that creates task directories and seeds a PRD. No destructive, exfiltrating, or obfuscated commands are present. The execution of a repository-specific script is a legitimate but filesystem-modifying action, so caution is warranted.
- •Instructs execution of a local Python script (./.trellis/scripts/task.py) via bash, which creates directories and modifies the filesystem without explicit user confirmation; benign only if the repository's task.py is trusted.
Examples
I want to add team workspaces to our app, but I'm not sure how sharing and permissions should work yet. Help me figure out what we're actually building.We need to ship notifications. Email, in-app, or both? Interview me and converge on an MVP for this.Brainstorm the requirements for migrating our billing from flat plans to usage-based pricing — trade-offs matter here.name: trellis-brainstorm description: "Guides collaborative requirements discovery before implementation. Creates task directory, seeds PRD, asks high-value questions one at a time, researches technical choices, and converges on MVP scope. Use when requirements are unclear, there are multiple valid approaches, or the user describes a new feature or complex task."
Brainstorm - Requirements Discovery (AI Coding Enhanced)
CoreRule: Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time.
If a question can be answered by exploring the codebase, explore the codebase instead.
Guide AI through collaborative requirements discovery before implementation, optimized for AI coding workflows:
- Task-first (capture ideas immediately)
- Action-before-asking (reduce low-value questions)
- Research-first for technical choices (avoid asking users to invent options)
- Diverge → Converge (expand thinking, then lock MVP)
When to Use
Triggered from /trellis:start when the user describes a development task, especially when:
- requirements are unclear or evolving
- there are multiple valid implementation paths
- trade-offs matter (UX, reliability, maintainability, cost, performance)
- the user might not know the best options up front
Core Principles (Non-negotiable)
-
Task-first (capture early) Always ensure a task exists at the start so the user's ideas are recorded immediately.
-
Action before asking If you can derive the answer from repo code, docs, configs, conventions, or quick research — do that first.
-
One question per message Never overwhelm the user with a list of questions. Ask one, update PRD, repeat.
-
Prefer concrete options For preference/decision questions, present 2–3 feasible, specific approaches with trade-offs.
-
Research-first for technical choices If the decision depends on industry conventions / similar tools / established patterns, do research first, then propose options.
-
Diverge → Converge After initial understanding, proactively consider future evolution, related scenarios, and failure/edge cases — then converge to an MVP with explicit out-of-scope.
-
No meta questions Do not ask "should I search?" or "can you paste the code so I can continue?" If you need information: search/inspect. If blocked: ask the minimal blocking question.
Step 0: Ensure Task Exists (ALWAYS)
Before any Q&A, ensure a task exists. If none exists, create one immediately.
- Use a temporary working title derived from the user's message.
- It's OK if the title is imperfect — refine later in PRD.
TASK_DIR=$(python3 ./.trellis/scripts/task.py create "brainstorm: <short goal>" --slug <auto>)
Use a slug without a date prefix. task.py create adds the MM-DD-
directory prefix automatically.
Create/seed prd.md immediately with what you know:
# brainstorm: <short goal>
## Goal
<one paragraph: what + why>
## What I already know
* <facts from user message>
* <facts discovered from repo/docs>
## Assumptions (temporary)
* <assumptions to validate>
## Open Questions
* <ONLY Blocking / Preference questions; keep list short>
## Requirements (evolving)
* <start with what is known>
## Acceptance Criteria (evolving)
* [ ] <testable criterion>
## Definition of Done (team quality bar)
* Tests added/updated (unit/integration where appropriate)
* Lint / typecheck / CI green
* Docs/notes updated if behavior changes
* Rollout/rollback considered if risky
## Out of Scope (explicit)
* <what we will not do in this task>
## Technical Notes
* <files inspected, constraints, links, references>
* <research notes summary if applicable>
Step 1: Auto-Context (DO THIS BEFORE ASKING QUESTIONS)
Before asking questions like "what does the code look like?", gather context yourself:
Repo inspection checklist
- Identify likely modules/files impacted
- Locate existing patterns (similar features, conventions, error handling style)
- Check configs, scripts, existing command definitions
- Note any constraints (runtime, dependency policy, build tooling)
Documentation checklist
- Look for existing PRDs/specs/templates
- Look for command usage examples, README, ADRs if any
Write findings into PRD:
- Add to
What I already know - Add constraints/links to
Technical Notes
Step 2: Classify Complexity (still useful, not gating task creation)
| Complexity | Criteria | Action | | ------------ | ------------------------------------------------------ | ------------------------------------------- | | Trivial | Single-line fix, typo, obvious change | Skip brainstorm, implement directly | | Simple | Clear goal, 1–2 files, scope well-defined | Ask 1 confirm question, then implement | | Moderate | Multiple files, some ambiguity | Light brainstorm (2–3 high-value questions) | | Complex | Vague goal, architectural choices, multiple approaches | Full brainstorm |
Note: Task already exists from Step 0. Classification only affects depth of brainstorming.
Step 3: Question Gate (Ask ONLY high-value questions)
Before asking ANY question, run the following gate:
Gate A — Can I derive this without the user?
If answer is available via:
- repo inspection (code/config)
- docs/specs/conventions
- quick market/OSS research
→ Do not ask. Fetch it, summarize, update PRD.
Gate B — Is this a meta/lazy question?
Examples:
- "Should I search?"
- "Can you paste the code so I can proceed?"
- "What does the code look like?" (when repo is available)
→ Do not ask. Take action.
Gate C — What type of question is it?
- Blocking: cannot proceed without user input
- Preference: multiple valid choices, depends on product/UX/risk preference
- Derivable: should be answered by inspection/research
→ Only ask Blocking or Preference.
Step 4: Research-first Mode (Mandatory for technical choices)
Trigger conditions (any → research-first)
- The task involves selecting an approach, library, protocol, framework, template system, plugin mechanism, or CLI UX convention
- The user asks for "best practice", "how others do it", "recommendation"
- The user can't reasonably enumerate options
Delegate to trellis-research sub-agent (don't research inline)
For each research topic, spawn a trellis-research sub-agent via the Task tool — don't do WebFetch / WebSearch / gh api inline in the main conversation.
Why:
- The sub-agent has its own context window → doesn't pollute brainstorm context with raw tool output
- It persists findings to
{TASK_DIR}/research/<topic>.md(the contract — seeworkflow.mdPhase 1.2) - It returns only
{file path, one-line summary}to the main agent - Independent topics can be parallelized — spawn multiple sub-agents in one tool call
Codex exception: on Codex CLI, do NOT dispatch
trellis-researchfor research-first mode — do the research inline (WebFetch / WebSearch in the main session) and write findings to{TASK_DIR}/research/<topic>.mdyourself. Reason: Codexspawn_agentruns sub-agents withfork_turns="none"(isolated context, no parent session inheritance), so the research sub-agent cannot resolve the active task path viatask.py currentand silently aborts without producing files. Inline research on Codex avoids this failure mode. The 3+ inline research calls limit (B rule inworkflow.md) is relaxed for Codex specifically.
Agent type: trellis-research
Task description template: "Research <specific question>; persist findings to {TASK_DIR}/research/<topic-slug>.md."
❌ Bad (what you must NOT do):
Main agent: WebFetch(url-A) → WebFetch(url-B) → Bash(gh api ...)
→ WebSearch(q1) → WebSearch(q2) → ... (10+ inline calls)
→ Write(research/topic.md)
→ Pollutes main context with raw HTML/JSON, burns tokens.
✅ Good:
Main agent: Task(subagent_type="trellis-research",
prompt="Research topic A; persist to research/topic-a.md")
+ Task(subagent_type="trellis-research",
prompt="Research topic B; persist to research/topic-b.md")
+ Task(subagent_type="trellis-research",
prompt="Research topic C; persist to research/topic-c.md")
→ Reads research/topic-{a,b,c}.md after they finish.
Research steps (to pass into each sub-agent prompt)
Each trellis-research sub-agent should:
- Identify 2–4 comparable tools/patterns for its topic
- Summarize common conventions and why they exist
- Map conventions onto our repo constraints
- Write findings to
{TASK_DIR}/research/<topic>.md
Main agent then reads the persisted files and produces 2–3 feasible approaches in PRD.
Research output format (PRD)
The PRD itself should only reference the persisted research files, not duplicate their content. Add a ## Research References section pointing at research/*.md.
Optionally, add a convergence section with feasible approaches derived from the research:
## Research References
* [`research/<topic-a>.md`](research/<topic-a>.md) — <one-line takeaway>
* [`research/<topic-b>.md`](research/<topic-b>.md) — <one-line takeaway>
## Research Notes
### What similar tools do
* ...
* ...
### Constraints from our repo/project
* ...
### Feasible approaches here
**Approach A: <name>** (Recommended)
* How it works:
* Pros:
* Cons:
**Approach B: <name>**
* How it works:
* Pros:
* Cons:
**Approach C: <name>** (optional)
* ...
Then ask one preference question:
- "Which approach do you prefer: A / B / C (or other)?"
Step 5: Expansion Sweep (DIVERGE) — Required after initial understanding
After you can summarize the goal, proactively broaden thinking before converging.
Expansion categories (keep to 1–2 bullets each)
-
Future evolution
- What might this feature become in 1–3 months?
- What extension points are worth preserving now?
-
Related scenarios
- What adjacent commands/flows should remain consistent with this?
- Are there parity expectations (create vs update, import vs export, etc.)?
-
Failure & edge cases
- Conflicts, offline/network failure, retries, idempotency, compatibility, rollback
- Input validation, security boundaries, permission checks
Expansion message template (to user)
I understand you want to implement: <current goal>.
Before diving into design, let me quickly diverge to consider three categories (to avoid rework later):
1. Future evolution: <1–2 bullets>
2. Related scenarios: <1–2 bullets>
3. Failure/edge cases: <1–2 bullets>
For this MVP, which would you like to include (or none)?
1. Current requirement only (minimal viable)
2. Add <X> (reserve for future extension)
3. Add <Y> (improve robustness/consistency)
4. Other: describe your preference
Then update PRD:
- What's in MVP →
Requirements - What's excluded →
Out of Scope
Step 6: Q&A Loop (CONVERGE)
Rules
-
One question per message
-
Prefer multiple-choice when possible
-
After each user answer:
- Update PRD immediately
- Move answered items from
Open Questions→Requirements - Update
Acceptance Criteriawith testable checkboxes - Clarify
Out of Scope
Question priority (recommended)
- MVP scope boundary (what is included/excluded)
- Preference decisions (after presenting concrete options)
- Failure/edge behavior (only for MVP-critical paths)
- Success metrics & Acceptance Criteria (what proves it works)
Preferred question format (multiple choice)
For <topic>, which approach do you prefer?
1. **Option A** — <what it means + trade-off>
2. **Option B** — <what it means + trade-off>
3. **Option C** — <what it means + trade-off>
4. **Other** — describe your preference
Step 7: Propose Approaches + Record Decisions (Complex tasks)
After requirements are clear enough, propose 2–3 approaches (if not already done via research-first):
Based on current information, here are 2–3 feasible approaches:
**Approach A: <name>** (Recommended)
* How:
* Pros:
* Cons:
**Approach B: <name>**
* How:
* Pros:
* Cons:
Which direction do you prefer?
Record the outcome in PRD as an ADR-lite section:
## Decision (ADR-lite)
**Context**: Why this decision was needed
**Decision**: Which approach was chosen
**Consequences**: Trade-offs, risks, potential future improvements
Step 8: Final Confirmation + Implementation Plan
When open questions are resolved, confirm complete requirements with a structured summary:
Final confirmation format
Here's my understanding of the complete requirements:
**Goal**: <one sentence>
**Requirements**:
* ...
* ...
**Acceptance Criteria**:
* [ ] ...
* [ ] ...
**Definition of Done**:
* ...
**Out of Scope**:
* ...
**Technical Approach**:
<brief summary + key decisions>
**Implementation Plan (small PRs)**:
* PR1: <scaffolding + tests + minimal plumbing>
* PR2: <core behavior>
* PR3: <edge cases + docs + cleanup>
Does this look correct? If yes, I'll proceed with implementation.
Subtask Decomposition (Complex Tasks)
For complex tasks with multiple independent work items, create subtasks:
# Create child tasks
CHILD1=$(python3 ./.trellis/scripts/task.py create "Child task 1" --slug child1 --parent "$TASK_DIR")
CHILD2=$(python3 ./.trellis/scripts/task.py create "Child task 2" --slug child2 --parent "$TASK_DIR")
# Or link existing tasks
python3 ./.trellis/scripts/task.py add-subtask "$TASK_DIR" "$CHILD_DIR"
PRD Target Structure (final)
prd.md should converge to:
# <Task Title>
## Goal
<why + what>
## Requirements
* ...
## Acceptance Criteria
* [ ] ...
## Definition of Done
* ...
## Technical Approach
<key design + decisions>
## Decision (ADR-lite)
Context / Decision / Consequences
## Out of Scope
* ...
## Technical Notes
<constraints, references, files, research notes>
Anti-Patterns (Hard Avoid)
- Asking user for code/context that can be derived from repo
- Asking user to choose an approach before presenting concrete options
- Meta questions about whether to research
- Staying narrowly on the initial request without considering evolution/edges
- Letting brainstorming drift without updating PRD
Integration with Start Workflow
After brainstorm completes (Step 8 confirmation approved), the flow continues to the Task Workflow's Phase 2: Prepare for Implementation:
Brainstorm
Step 0: Create task directory + seed PRD
Step 1–7: Discover requirements, research, converge
Step 8: Final confirmation → user approves
↓
Task Workflow Phase 2 (Prepare for Implementation)
Code-Spec Depth Check (if applicable)
→ Research codebase (based on confirmed PRD)
→ Configure code-spec context (jsonl files)
→ Activate task
↓
Task Workflow Phase 3 (Execute)
Implement → Check → Complete
The task directory and PRD already exist from brainstorm, so Phase 1 of the Task Workflow is skipped entirely.
Related Commands
| Command | When to Use |
|---------|-------------|
| /trellis:start | Entry point that triggers brainstorm |
| /trellis:finish-work | After implementation is complete |
| /trellis:update-spec | If new patterns emerge during work |
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/brainstorm-requirements-discovery-ms71b2z5/download' --output '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md.part' && mv '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md.part' '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md' && test -s '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/trellis-brainstorm' && cp -R '.skill-downloads/brainstorm-requirements-discovery-ms71b2z5' '.claude/skills/trellis-brainstorm'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/brainstorm-requirements-discovery-ms71b2z5'openskills read 'brainstorm-requirements-discovery-ms71b2z5'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.
openskills syncManual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/brainstorm-requirements-discovery-ms71b2z5/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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