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 OneWave-AI/claude-skills --skill pricing-change-strategistgit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/pricing-change-strategist)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/pricing-change-strategist"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/pricing-change-strategist/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/onewave-ai/claude-skills/pricing-change-strategist"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/pricing-change-strategist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00083 | $0.01075 |
| Opus 5 | $0.00042 | $0.00537 |
| Sonnet 5 | $0.00017 | $0.00215 |
| Haiku 4.5 | $0.00008 | $0.00108 |
Grade A, and why
pricing-change-strategist 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pricing Change Strategist
Raising prices is the highest-leverage move most companies are too scared to make well. Done carelessly it churns your base and lights up Twitter. Done well it's nearly pure margin. This skill plans the change end to end — the math, the segmentation, the grandfathering call, and every word customers will read.
Pair it with product-launch-war-room (to decide whether) and customer-panel-of-experts (to hear how each segment reacts). This skill owns the how.
Step 1 — Establish the baseline
Gather (read-only from billing/CRM where connected — Stripe, Mercury, Supabase via $SUPABASE_TOKEN; otherwise ask):
- Current pricing, tiers, and discount reality (list vs. actual realized).
- Revenue distribution: ACV by segment, concentration, % on legacy/grandfathered plans.
- Churn and expansion rates by segment.
- Cost-to-serve by tier (where the margin actually is).
- The trigger: why now — cost, value delivered, repositioning, market.
Security: read-only. Never modify subscriptions, prices, or send anything. No real customer PII in artifacts — segment in aggregate. Secrets in env vars only.
Step 2 — Segment by price sensitivity
Split the base into action groups, e.g.:
- Anchor accounts — high revenue, high switching cost → can absorb increase, handle white-glove.
- Price-sensitive core — value-conscious, mobile → highest churn risk, needs the strongest value story.
- Legacy / underpriced — paying far below current value → biggest opportunity, biggest betrayal risk.
- At-risk — already low engagement → may use the increase as an exit cue; decide if you want to keep them.
For each: current price, proposed price, % change, estimated churn response, net revenue impact.
Step 3 — Model the scenarios
Build a simple, transparent model (write it out so the math is auditable — never hand-wave aggregates):
- Conservative / expected / aggressive increase levels.
- For each: projected churn %, retained revenue, net new revenue, payback on any concessions.
- The break-even churn: how much churn the increase can absorb before it's net-negative.
- Sensitivity: which assumption the outcome hinges on most.
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.
- 9d ago First seen · 83 lines · 83 tokens per session scan A d564f82cdbef
pricing-change-strategist is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 1,075 once invoked, about $0.0004 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 2026-09-03.
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