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 Grafuja/Product-Manager-Skills --skill rice-calculator-coachgit clone --depth 1 https://github.com/Grafuja/Product-Manager-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/grafuja/product-manager-skills/rice-calculator-coach)<a href="https://agentmods.dev/skills/grafuja/product-manager-skills/rice-calculator-coach"><img src="https://agentmods.dev/badge/skills/grafuja/product-manager-skills/rice-calculator-coach/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/grafuja/product-manager-skills/rice-calculator-coach"><img src="https://agentmods.dev/badge/skills/grafuja/product-manager-skills/rice-calculator-coach.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 | $0.00096 | $0.03698 |
| Opus 5 | $0.00048 | $0.01849 |
| Sonnet 5 | $0.00019 | $0.00740 |
| Haiku 4.5 | $0.00010 | $0.00370 |
Grade A, and why
rice-calculator-coach 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.
How it starts
The opening of the file, as written. The whole thing — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RICE Calculator Coach
An interactive guide that helps product managers calculate RICE scores for their initiatives with context-aware explanations and benchmarks.
Core Workflow
When triggered, follow this conversational flow:
Step 1: Capture the Initiative
Ask: "What initiative do you want to score?"
If they give a feature/output (e.g., "API de integraciones"), help them reframe as an outcome:
- "Let's frame this as an outcome. What problem does this solve and for whom?"
- Guide them to: "[Action] [metric] de [X] a [Y] para [user] en [timeframe]"
Example transformation:
- ❌ Input: "Dashboard de reportes"
- ✅ Output: "Reducir tiempo de generación de reportes de 30 min a 5 min para CFOs en Q2"
Store: initiative_name and initiative_outcome
Step 2: Calculate Reach
Ask: "How many users/customers will this impact per quarter?"
Provide context based on their product type:
For B2B SaaS:
- "Total active customers: ___
- Affected by this initiative: ___% = ___ customers/quarter"
For B2C/Consumer:
- "Monthly active users: ___
- Affected by this initiative: ___% = ___ users/quarter"
For Internal Tools:
- "Team members using the tool: ___
- Affected by this initiative: ___% = ___ people/quarter"
If they're uncertain:
- Offer estimation help: "Let's estimate. Do you have [X] metric we can use?"
- Provide ranges: "Low (100-500), Medium (500-2K), High (2K-10K), Very High (10K+)"
Common mistakes to catch:
- Using monthly instead of quarterly (multiply by 3)
- Confusing total users with affected users
- Including users who won't actually use the feature
Store: reach (as number)
Show calculation so far:
Initiative: [name]
Reach: [number] users/quarter
Step 3: Determine Impact
Ask: "How much will this improve things for each user?"
Present the scale with examples:
Impact Scale:
- 3.0 = Massive - Core value prop, 10x improvement
- Example: "Reduce task time from 4 hours to 15 minutes"
- Example: "Feature blocks $500K in enterprise deals"
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 · 492 lines · 96 tokens per session scan A 67741ece207e
rice-calculator-coach is a skill published in the GitHub repository Grafuja/Product-Manager-Skills (9 stars, last pushed 5mo ago), licensed MIT. It adds 96 tokens to every session and 3,698 once invoked, about $0.0005 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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