| name | make-proposals |
| description | Generate up to two solution proposals grounded in prior research (with architecture diagrams). Use after research, before planning. |
Generate two solution proposals grounded in existing research and a feature or project request.
Behavior
- Require a research document produced by
/research-codebase (either a local file path or a Linear document).
- Produce two distinct solution approaches, each tied back to the research findings.
- Highlight trade-offs, impacted systems, validation steps, and open questions per proposal.
Steps
- Intake
- Capture the user's request. If a Linear issue or project is referenced and Linear MCP tools are available, read it.
- Read the research document (local file or Linear document).
- Parse research
- Extract constraints, relevant modules, dependencies, data flows, and prior decisions.
- Synthesize solution space
- Derive candidate approaches grounded in the research findings.
- For each approach, note primary changes, affected code paths, required migrations/config updates, and rollout considerations.
- Keep the list to two distinct proposals, ordered from most to least aligned with constraints.
- Validation planning
- Identify verification strategies (tests, experiments, observability) necessary to prove each approach.
- Surface critical unknowns or prerequisite research.
- Save proposals:
- If Linear MCP tools are available, save as a Linear document.
- Also save locally for reference.
- Present the proposals to the user for a decision.
Output template
## Solution Proposals
Context:
- Request: <short restatement of the ask>
- Research Source: <document or filename and key sections used>
Proposal 1 — <title>
- Overview: <2-3 sentences>
- Key Changes: <components/modules>
- Trade-offs: <risks vs benefits>
- Validation: <tests/experiments/metrics>
- Open Questions: <gaps or follow-ups>
Proposal 2 — <title>
...
Notes
- Reference code and sections using
path/to/file.py:lines when citing specifics.
- When the research does not directly address the request, call out the gaps and suggest additional research before proposing solutions.
- Stay concise; favor clarity over exhaustive detail.
