Turning Renovation Ideas into Viable Options with an Agent Skill

Where this fits

A homeowner sends a photo of their dated bathroom and a single line: "I want it to feel like a spa, but I don't know where to start." A generic assistant might suggest tiles and faucets. This skill instead structures the ambiguity into distinct renovation scenarios — each with its own constraints, implied trades, and trade-offs. It works for any brief input about a room, an exterior, an energy concern, or a discomfort, as long as the user is not asking for a fixed price or a step-by-step execution order.

Why agents benefit

• Turns vague input into structured options: The skill separates what is visible or provided from assumptions and on-site verifications, so the agent can present options without fabricating technical certainties.
• Forces meaningful alternatives: Instead of a laundry list of ideas, the agent builds two or three sharply different scenarios, each with a coherent direction (e.g., full remodel vs. targeted refresh vs. layout change).
• Explicitly compares trade-offs: Each scenario is evaluated on usage, maintenance, relative cost, and induced work — the kind of comparison a homeowner actually needs before calling a contractor.
• Honestly distinguishes knowns from unknowns: The agent learns to flag what needs a professional site visit, avoiding overconfident advice on load-bearing walls or plumbing reroutes.
• Respects the skill's boundary conditions: It clearly stops when the user asks for a price estimate, a rule-based order of operations, or contractor comparison — redirecting to what the skill can safely do.

Practical scenarios

A quick kitchen idea on a lunch break

User says: "Our kitchen feels dark and cramped. We cook a lot." The skill asks about what must stay, then produces two scenarios: opening a partition (with structural verification flagged) vs. reorganizing the layout and improving lighting (lower induced work).

An energy comfort complaint

User mentions drafty windows and cold floors in the living room. The skill differentiates between insulation, heating, and window replacement as separate axes, building scenarios that combine them with relative cost and disruption.

A garden or terrace wish

A photo of an empty backyard triggers scenarios for a low-maintenance patio, a vegetable garden with water access, or a shaded leisure zone — each listing likely trades like masonry or landscaping.

Add it to your agent workflow

Install the skill with:

npx skills add mehdimicra/renoolab-agent-skills --skill renoolab-imaginer-arbitrer-renovation

Then in your agent's system prompt or tool definitions, note that it should be loaded whenever a user mentions a space, a style, or a comfort issue. For example:

When the user describes any renovation ambition (even one sentence), use the skill to generate two or three compared scenarios, each with constraints, implied lots, and probable trades. Separate verified facts from assumptions.

Compare before adopting

Look at how the skill handles your test cases: does it ask clarifying questions when needed? Does it avoid inventing costs? Does it clearly state which elements require a professional survey? Also check the GitHub repo's activity and whether examples cover your typical agent use cases. You can explore the skill's page on OpenAgentSkill to see how its documentation aligns with your workflow.

Why it is worth tracking

This skill addresses a common blind spot in renovation assistants: turning inspiration into a decision framework rather than giving premature advice. The project is early (3 stars) but its design shows careful scoping of what the skill will and won't do — a good signal for a purpose-built tool. Track it if you build agents for home improvement, interior design, or energy retrofits, and re-evaluate once the author adds more examples or user feedback.