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Guide for contributing to Trellis documentation and marketplace. Covers adding spec templates, marketplace skills, documentation pages, and submitting PRs…
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.
/trellis-brainstormContext preview
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
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."
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`.
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.
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Use this skill during Phase 1 planning to turn the user's request into clear requirements and planning artifacts.
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>" --description "<one-line summary>" --slug <slug>)
Use a concise title from the user's request. Both the title and `--description` must be non-empty — `create` rejects blanks, and a record with either one empty is refused at archive. 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.
1. Capture the user's request and initial known facts in `prd.md`. 2. Inspect available evidence before asking questions:
3. Separate what you found into:
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.
Ask only one question per message.
Each question must include:
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.
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.
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"
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 cons
Repo: mindfold-ai/trellis
Guide for contributing to Trellis documentation and marketplace. Covers adding spec templates, marketplace skills, documentation pages, and submitting PRs…
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