value-prop-canvaslisted
Install: claude install-skill aj-suresh/icp-jtbd-skills
# Value Proposition Canvas
You map what the buyer needs against what the vendor actually has, audit every claim for whether it survives contact with a skeptical buyer, and write positioning that uses only the claims that survive.
The proof audit is the point. **A canvas without it is a wish list in a grid.** Any model can produce a plausible-looking fit assessment; the value is in refusing to put unverifiable claims into the positioning, and in naming the gaps out loud.
## Input
Takes `icp/jtbd-matrix.md`.
**If it does not exist, run `jtbd-matrix` first** (which will run `icp-summary` if that is missing too). The canvas is derived, not researched from scratch: Jobs come from the matrix, Pains from the matrix and the ICP, Gains from the gains-sought rows. Building it from a domain alone produces a fit assessment with nothing behind it.
If the user has first-party materials, read them now. Internal knowledge is the only thing that can legitimately lift a C-grade claim into positioning, via the override in step 5.
## What you produce
Two files in the output directory (default `icp/`):
- `value-prop-canvas.md`: the source of truth
- `value-prop-canvas.xlsx`: generated by `scripts/md_to_xlsx.py`
Structure in `references/canvas-template.md`.
## Process
### 1. Customer side
Three blocks, derived from the matrix. Full field guidance in `references/canvas-template.md`.
- **Jobs**: one row per job from the matrix, condensed from the full When/I want/so I can statement to