Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tjboudreaux/cc-plugin-product-strategist --skill product-value-propositiongit clone --depth 1 https://github.com/tjboudreaux/cc-plugin-product-strategistWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tjboudreaux/cc-plugin-product-strategist/product-value-proposition)<a href="https://agentmods.dev/skills/tjboudreaux/cc-plugin-product-strategist/product-value-proposition"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-plugin-product-strategist/product-value-proposition/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tjboudreaux/cc-plugin-product-strategist/product-value-proposition"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-plugin-product-strategist/product-value-proposition.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.00304 |
| Opus 5 | $0.00010 | $0.00152 |
| Sonnet 5 | $0.00004 | $0.00061 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
product-value-proposition scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Value Proposition Lab
Intent
- Turn opportunity theses into sharp promises that resonate with target personas and platforms.
- Use lightweight artifacts (narratives, prototypes, landing pages) to test resonance and pricing early.
Inputs
- Target persona canvas + JTBD statements.
- Competitive teardown (positioning, pricing, retention hooks).
- Measurement plan (success metrics, experiment KPIs, survey scripts).
Workflow
- Promise crafting
- Write 3–5 alternative promise statements highlighting outcome, emotional payoff, and proof.
- Stress-test for clarity, distinctiveness, believability.
- Artifact production
- Choose fastest medium: storyboard, Figma mock, interactive prototype, gameplay video, tokenomics sim.
- Include pricing/commitment ask if relevant.
- Signal testing
- Run rapid qualitative tests (5–8 target users) plus at least one quantitative signal (ad test, waitlist opt-in, fake door).
- Collect friction language and willingness-to-pay indicators.
- Decision log
- Rank propositions by signal strength vs. confidence; document go/hold/kill decisions.
Verification
- Experiments include control + clear success thresholds.
- Learnings and next steps stored in shared experiment log.
- Downstream teams notified when a proposition graduates to build stage.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 34 lines · 21 tokens per session scan A 67f805c553ff
product-value-proposition is a skill published in the GitHub repository tjboudreaux/cc-plugin-product-strategist (2 stars, last pushed 7mo ago), licensed MIT. It adds 21 tokens to every session and 304 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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