/trellis-brainstorm
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
$ npx -y skills add mindfold-ai/trellis --skill trellis-brainstorm --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/trellis-brainstorm
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The summary Claude sees to decide when to auto-load this skill.
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
SKILL.md
trellis-brainstorm.SKILL.mdname: 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."
Trellis Brainstorm
Non-Negotiable Planning Contract
A request to build, implement, fix, refactor, or "go ahead" is not approval to leave planning. Task-creation consent is also not implementation approval.
For every non-trivial task, the user must respond at least once after the initial request before implementation begins. If no clarification is needed, that response must approve the final planning summary described below.
While any user-owned product, scope, UX, compatibility, risk, or acceptance decision remains unresolved, end the turn with exactly one highest-value question. Do not edit product code, dispatch implementation, or run `task.py start`.
Non-Negotiable Evidence Rule
If a question can be answered by exploring the codebase, explore the codebase instead.
This is mandatory. Before asking the user a question, first check whether the answer is already available in code, tests, configs, docs, existing specs, or task history.
Do not ask the user to confirm facts that the repository can answer. Ask only for product intent, preference, scope, risk tolerance, acceptance behavior, or decisions that remain ambiguous after inspection.
Repository evidence establishes current behavior and technical constraints. The user's intended behavior, feature scope boundaries, and UX preferences are never answerable by repository evidence alone, even when an existing pattern exists; existing patterns are options and recommendation evidence, not decisions.
---
Use this skill during Phase 1 planning to turn the user's request into clear requirements and planning artifacts.
Preconditions
Use this skill only after task-creation consent has been given and the user is ready to enter Trellis planning.
If no task exists yet, create one:
TASK_DIR=$(python3 ./.trellis/scripts/task.py create "<short task title>" --slug <slug>)
Use a concise title from the user's request. Use a slug without a date prefix. `task.py create` adds the `MM-DD-` directory prefix automatically.
`task.py create` creates the default `prd.md`. Update that file with the current understanding before asking follow-up questions.
Planning Flow
1. Capture the user's request and initial known facts in `prd.md`. 2. Inspect available evidence before asking questions:
- code, tests, fixtures, and configs
- README files, docs, existing specs, and domain notes
- related Trellis tasks, research files, and session history when present
3. Separate what you found into:
- confirmed facts
- product intent still needed from the user
- scope or risk decisions still needed from the user
- likely out-of-scope items
4. If a user-owned decision remains, ask the single highest-value question, include your recommendation and trade-off, then stop. Do not perform implementation work in the same turn. 5. After each user answer, update `prd.md`, recompute the decision inventory, and repeat from step 2. 6. When no user-owned decision remains, create or update `design.md` and `implement.md` for complex tasks. 7. Run the requirement convergence gate, then the PRD convergence pass. 8. Present the final planning summary and stop. Do not run `task.py start` or edit product code in the same turn. 9. Only a subsequent user message that explicitly approves the latest planning summary authorizes `task.py start` and implementation. If the artifacts change materially after approval, repeat the final review.
Do not invent a project-specific product/spec hierarchy. If the repository already has product, domain, or spec docs, use them. If it does not, proceed with the evidence that exists.
Question Rules
Ask only one question per message.
Each question must include:
- the decision needed
- why the answer matters
- your recommended answer
- the trade-off if the user chooses differently
Do not ask process questions such as whether to search, inspect files, or continue brainstorming. Do the evidence work directly. Ask the user only when the remaining issue is a product decision, preference, scope boundary, or risk tolerance choice.
Recommendations are not default selections. Never choose a recommended product decision on the user's behalf merely because the user asked for implementation.
Do not manufacture clarification questions when the request and repository evidence already resolve every decision. In that case, proceed directly to the final planning summary, which still requires a subsequent explicit approval.
The final review is a required phase-transition gate, not a prohibited process question. Task-creation consent, the initial implementation request, and approval given before the latest final summary do not satisfy this gate.
Thinking Framework: First Principles Analysis
When requirements are vague, solutions feel over-engineered, or you're about to add complexity "because everyone does" — decompose to fundamental truths before reasoning upward.
Step 1: Restate the Problem
Strip away implementation details to one sentence.
> Bad: "We need to add Redis caching to the user profile endpoint" > Good: "User profile data takes too long to load"
Step 2: List Fundamental Truths
What is absolutely true (not opinion or convention)?
| Category | Examples | |----------|----------| | **Physical constraints** | Network latency ≥ 0, disk I/O has limits | | **Business rules** | "Users must see their own data" | | **Technical invariants** | "Data must be consistent" | | **User needs** | "The user wants X within Y seconds" |
Step 3: Challenge Assumptions
For each component of the current plan:
- **Fact or convention?** "We
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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."
Trellis Brainstorm
Non-Negotiable Planning Contract
A request to build, implement, fix, refactor, or "go ahead" is not approval to leave planning. Task-creation consent is also not implementation approval.
For every non-trivial task, the user must respond at least once after the initial request before implementation begins. If no clarification is needed, that response must approve the final planning summary described below.
While any user-owned product, scope, UX, compatibility, risk, or acceptance decision remains unresolved, end the turn with exactly one highest-value question. Do not edit product code, dispatch implementation, or run `task.py start`.
Non-Negotiable Evidence Rule
If a question can be answered by exploring the codebase, explore the codebase instead.
This is mandatory. Before asking the user a question, first check whether the answer is already available in code, tests, configs, docs, existing specs, or task history.
Do not ask the user to confirm facts that the repository can answer. Ask only for product intent, preference, scope, risk tolerance, acceptance behavior, or decisions that remain ambiguous after inspection.
Repository evidence establishes current behavior and technical constraints. The user's intended behavior, feature scope boundaries, and UX preferences are never answerable by repository evidence alone, even when an existing pattern exists; existing patterns are options and recommendation evidence, not decisions.
---
Use this skill during Phase 1 planning to turn the user's request into clear requirements and planning artifacts.
Preconditions
Use this skill only after task-creation consent has been given and the user is ready to enter Trellis planning.
If no task exists yet, create one:
TASK_DIR=$(python3 ./.trellis/scripts/task.py create "<short task title>" --slug <slug>)
Use a concise title from the user's request. Use a slug without a date prefix. `task.py create` adds the `MM-DD-` directory prefix automatically.
`task.py create` creates the default `prd.md`. Update that file with the current understanding before asking follow-up questions.
Planning Flow
1. Capture the user's request and initial known facts in `prd.md`. 2. Inspect available evidence before asking questions:
- code, tests, fixtures, and configs
- README files, docs, existing specs, and domain notes
- related Trellis tasks, research files, and session history when present
3. Separate what you found into:
- confirmed facts
- product intent still needed from the user
- scope or risk decisions still needed from the user
- likely out-of-scope items
4. If a user-owned decision remains, ask the single highest-value question, include your recommendation and trade-off, then stop. Do not perform implementation work in the same turn. 5. After each user answer, update `prd.md`, recompute the decision inventory, and repeat from step 2. 6. When no user-owned decision remains, create or update `design.md` and `implement.md` for complex tasks. 7. Run the requirement convergence gate, then the PRD convergence pass. 8. Present the final planning summary and stop. Do not run `task.py start` or edit product code in the same turn. 9. Only a subsequent user message that explicitly approves the latest planning summary authorizes `task.py start` and implementation. If the artifacts change materially after approval, repeat the final review.
Do not invent a project-specific product/spec hierarchy. If the repository already has product, domain, or spec docs, use them. If it does not, proceed with the evidence that exists.
Question Rules
Ask only one question per message.
Each question must include:
- the decision needed
- why the answer matters
- your recommended answer
- the trade-off if the user chooses differently
Do not ask process questions such as whether to search, inspect files, or continue brainstorming. Do the evidence work directly. Ask the user only when the remaining issue is a product decision, preference, scope boundary, or risk tolerance choice.
Recommendations are not default selections. Never choose a recommended product decision on the user's behalf merely because the user asked for implementation.
Do not manufacture clarification questions when the request and repository evidence already resolve every decision. In that case, proceed directly to the final planning summary, which still requires a subsequent explicit approval.
The final review is a required phase-transition gate, not a prohibited process question. Task-creation consent, the initial implementation request, and approval given before the latest final summary do not satisfy this gate.
Thinking Framework: First Principles Analysis
When requirements are vague, solutions feel over-engineered, or you're about to add complexity "because everyone does" — decompose to fundamental truths before reasoning upward.
Step 1: Restate the Problem
Strip away implementation details to one sentence.
> Bad: "We need to add Redis caching to the user profile endpoint" > Good: "User profile data takes too long to load"
Step 2: List Fundamental Truths
What is absolutely true (not opinion or convention)?
| Category | Examples | |----------|----------| | **Physical constraints** | Network latency ≥ 0, disk I/O has limits | | **Business rules** | "Users must see their own data" | | **Technical invariants** | "Data must be consistent" | | **User needs** | "The user wants X within Y seconds" |
Step 3: Challenge Assumptions
For each component of the current plan:
- **Fact or convention?** "We
Repo: mindfold-ai/trellis
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Open skill - /gitnexus-debugging
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: \"Why is X failing?\", \"Where does this error come from?\", \"Trace this bug\"
Open skill - /gitnexus-exploring
Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: \"How does X work?\", \"What calls this function?\", \"Show me the auth flow\"
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