Game Changing Features
openstatusHQ/data-table-filters
Find 10x product opportunities and high-leverage improvements.
Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions.
Install Value Proposition Canvas
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install borghei/Claude-Skills value-proposition-canvas --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .claude/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .claude/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvasType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install borghei/Claude-Skills value-proposition-canvas --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .agents/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .agents/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install borghei/Claude-Skills value-proposition-canvas --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .cursor/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .cursor/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/borghei/Claude-Skills.git --path project-management/discovery/value-proposition-canvas--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install borghei/Claude-Skills value-proposition-canvas --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .gemini/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .gemini/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install borghei/Claude-Skills value-proposition-canvasInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .github/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .github/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install borghei/Claude-Skills value-proposition-canvas --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/project-management/discovery/value-proposition-canvas .opencode/skills/value-proposition-canvas && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "value-proposition-canvas" agent skill from https://github.com/borghei/Claude-Skills/tree/main/project-management/discovery/value-proposition-canvas into .opencode/skills/value-proposition-canvas/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "value-proposition-canvas", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
value-proposition-canvas- GitHub stars
- 881
- Token cost
- ~1.7k tokens
- SKILL.md length
- 747 words
- Files
- 9 (incl. references, assets)
- Skills in repo
- 349
- Repo updated
- First seen
- Licence
- MIT
At a glance
Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions.
- Works in 3 steps: Pick one segment; run 5-7 interviews via… → Fill the Customer Profile… → Run assets/fit_validation_checklist.md,…
- Jobs-to-be-done
- SKILL.md covers Overview, Core Capabilities, When to Use and Clarify First, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Value Proposition Canvas is an agent skill from borghei/Claude-Skills. Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions. Use for jobs-to-be-done, pains/gains, and product-market-fit framing.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files and assets (for example `assets/customer_profile_worksheet.md`, `assets/fit_validation_checklist.md` and `assets/value_map_worksheet.md`).
It sits in Product & Project Management, covering Product strategy. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.
When your agent uses it
- Jobs-to-be-done
- Product-market-fit framing
Example prompts
- “/value-proposition-canvas”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Pick one segment; run 5-7 interviews via discovery/customer-interview-script/.
- Fill the Customer Profile (jobs/pains/gains, ranked) from discovery/interview-synthesis/ themes; then draft the Value Map so each top item…
- Run assets/fit_validation_checklist.md, list the top unaddressed pains/gains, and feed the canvas into execution/create-prd/ Sections 5-6.
What it can do on your machine
Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Value Proposition Canvas loads about 1.7k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 747 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 747 words, ~1,713 tokens.
Download SKILL.mdSave it as
.claude/skills/value-proposition-canvas/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- value-proposition-canvas
- description
- Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions. Use for jobs-to-be-done, pains/gains, and product-market-fit framing.
- license
- MIT + Commons Clause
- metadata.version
- 1.0.1
- metadata.author
- borghei
- metadata.category
- project-management
- metadata.domain
- pm-discovery
- metadata.updated
- 2026-06-15
- metadata.tech-stack
- value-proposition, jobs-to-be-done, strategyzer, product-market-fit
Value Proposition Canvas Expert
Overview
The Value Proposition Canvas (VPC) is the canonical Strategyzer tool for designing and testing the fit between what customers care about and what your product offers. It is the "zoom-in" companion to the Business Model Canvas, focused on the two most failure-prone blocks: Customer Segments and Value Propositions. Where the Business Model Canvas asks "is this a viable business?", the VPC asks "are we building something customers actually want?"
The canvas has two sides. The Customer Profile describes the customer's world in their language -- jobs they are trying to do, pains they experience, and gains they aspire to. The Value Map describes the product's response -- the products and services offered, the pain relievers they include, and the gain creators they enable. Fit is achieved when the Value Map mirrors the Customer Profile element-by-element. The method follows Alexander Osterwalder and Yves Pigneur's Value Proposition Design (2014).
Core Capabilities
- Customer Profile construction -- jobs (functional/social/emotional), pains, and gains, each ranked (importance, severity x frequency, desirability).
- Value Map construction -- products & services, pain relievers, and gain creators, each mapped to a specific profile element.
- Three-level fit validation -- problem-solution fit (interviews), product-market fit (behavior), business-model fit (unit economics).
- Artifacts -- markdown canvas template, worked example, and a fit-validation checklist that flags strong/partial/absent fit.
When to Use
- Pre-PRD framing -- validate the value proposition and customer profile before writing requirements.
- Solution refinement -- diagnose whether weak traction is a wrong-segment (Customer Profile) or wrong-response (Value Map) problem.
- New segment expansion -- build a separate VPC per segment to test fit.
- Pricing and packaging -- pains/gains rank-ordering informs which features go in which tier.
- Sales enablement -- pain relievers and gain creators become talking points and proof points.
Clarify First
Before building the canvas, confirm these inputs. If any is unknown or vague, ASK — do not assume:
- The one segment — the VPC is segment-level; one canvas per segment (defines whose Customer Profile you fill)
- Customer evidence source — interviews/synthesis vs team assumptions (jobs/pains/gains in the team's own words is the #1 way the canvas becomes fiction)
- Which fit level — problem-solution / product-market / business-model (sets the validation method: interviews vs behavior vs unit economics)
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Quick Start
- Pick one segment; run 5-7 interviews via
discovery/customer-interview-script/. - Fill the Customer Profile (jobs/pains/gains, ranked) from
discovery/interview-synthesis/themes; then draft the Value Map so each top item has a pain reliever or gain creator. - Run
assets/fit_validation_checklist.md, list the top unaddressed pains/gains, and feed the canvas intoexecution/create-prd/Sections 5-6.
See references/canvas-construction-playbook.md for the full two-side method, three fit levels, template, worked example, and troubleshooting.
Show full SKILL.md (298 more words)Show less
References
references/canvas-construction-playbook.md-- read this when building a canvas end-to-end: both sides in detail, the three levels of fit, the markdown canvas template, a full worked example (Finance Reconciliation SaaS), common mistakes, workflow, troubleshooting, and success criteria.references/value-proposition-design-guide.md-- read this for the deep Strategyzer methodology with additional worked examples.references/red-flags.md-- read this when reviewing a completed canvas for anti-patterns (team-language, forced fit, fit-level confusion) before relying on it.assets/vpc_template.md-- markdown canvas template.assets/customer_profile_worksheet.md-- jobs/pains/gains capture worksheet.assets/value_map_worksheet.md-- products/pain-relievers/gain-creators capture worksheet.assets/fit_validation_checklist.md-- three-level fit validation checklist.
Scope & Limitations
In scope: Customer Profile (jobs, pains, gains) construction and ranking; Value Map construction; problem-solution fit validation; mapping the canvas into PRD inputs (execution/create-prd/ Sections 5 and 6); sales-enablement translation.
Out of scope: Business Model Canvas (sister tool, 9 blocks); unit economics and business-model fit (finance/ skills); detailed financial modeling, LTV/CAC; persona generation (the VPC is segment-level); competitive positioning (marketing/ or c-level-advisor/competitive-strategy/).
Caveats: the VPC is a thinking aid, not a roadmap -- solutions still need experimentation (discovery/brainstorm-experiments/). Problem-solution fit is the minimum bar, necessary but not sufficient for product-market fit. Strategyzer methodology is CC-BY-SA; attribute to Strategyzer / Osterwalder when sharing externally. A beautifully filled canvas with no customer interviews is fiction.
Integration Points
| Integration | Direction | What Flows |
|---|---|---|
discovery/customer-interview-script/ | Receives from | Verbatim customer quotes populate the Customer Profile |
discovery/interview-synthesis/ | Receives from | Themed insights become jobs, pains, and gains |
discovery/jtbd-workshop/ | Complementary | JTBD workshop produces the job hierarchy; VPC adds pains and gains |
discovery/identify-assumptions/ | Bidirectional | Unaddressed pains become risk assumptions; assumptions inform validation focus |
execution/create-prd/ | Feeds into | Canvas populates PRD Section 5 (Market Segments) and Section 6 (Value Propositions) |
execution/product-vision/ | Bidirectional | Vision defines the long-term promise; VPC validates current-day delivery |
execution/prioritization-frameworks/ | Feeds into | Unaddressed top pains and gains become candidate features |
marketing/ | Feeds into | Pain relievers and gain creators become marketing talking points and proof points |
© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 8 other files (references, assets) in project-management/discovery/value-proposition-canvas of borghei/Claude-Skills.
- SKILL.md
- assets/customer_profile_worksheet.md
- assets/fit_validation_checklist.md
- assets/value_map_worksheet.md
- assets/vpc_template.md
- examples/dev-tools-platform-engineer-vpc.md
- references/canvas-construction-playbook.md
- references/red-flags.md
- references/value-proposition-design-guide.md
Open the folder on GitHubat commit 4a698e8
Compare with similar skills
Value Proposition Canvas next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Value Proposition Canvas this skillborghei/Claude-Skills | 881 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Game Changing FeaturesopenstatusHQ/data-table-filters | 2.3k | 3 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Company Research Briefdeanpeters/Product-Manager-Skills | 7.2k | 2 repos | ~3.8k | Automated safety check: Pass | Custom licence | |
| Organic Growth Path Advisordeanpeters/Product-Manager-Skills | 7.2k | 2 repos | ~5.2k | Automated safety check: Pass | Custom licence | |
| Product Strategistalirezarezvani/claude-skills | 28k | 2 repos | ~1.8k | Automated safety check: Pass | MIT | |
| PlaidBuildGreatProducts/plaid | 217 | — | ~1.6k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Value Proposition Canvas
What does Value Proposition Canvas do?
Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions. Value Proposition Canvas is an agent skill from borghei/Claude-Skills. Strategyzer Value Proposition Canvas (Customer Profile + Value Map) with fit validation across problem-solution, product-market, and business-model dimensions.
When should I use Value Proposition Canvas?
Value Proposition Canvas fits situations like: jobs-to-be-done; product-market-fit framing.
How do I install Value Proposition Canvas in Claude Code?
Run `npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a claude-code`. Or copy the skill folder (project-management/discovery/value-proposition-canvas in borghei/Claude-Skills) into .claude/skills/value-proposition-canvas in your project. Claude Code loads it when a task matches its description.
How do I install Value Proposition Canvas in Codex?
Run `npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a codex`. Or copy the skill folder (project-management/discovery/value-proposition-canvas in borghei/Claude-Skills) into .agents/skills/value-proposition-canvas in your project. Codex loads it when a task matches its description.
Can I use Value Proposition Canvas in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill value-proposition-canvas -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/value-proposition-canvas, .gemini/skills/value-proposition-canvas, .github/skills/value-proposition-canvas and .opencode/skills/value-proposition-canvas in your project.
What does Value Proposition Canvas need to run?
SKILL.md names no scripts, command-line tools or credentials: Value Proposition Canvas is instructions for the agent only.
Does Value Proposition Canvas access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Value Proposition Canvas safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Value Proposition Canvas use?
Value Proposition Canvas is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Value Proposition Canvas use?
About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.
What are the alternatives to Value Proposition Canvas?
Skills that share tags, products or a category with Value Proposition Canvas: Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars), Company Research Brief (deanpeters/Product-Manager-Skills, 7.2k stars), Organic Growth Path Advisor (deanpeters/Product-Manager-Skills, 7.2k stars) and Product Strategist (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Value Proposition Canvas?
borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.
Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.