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 sruthir28/enterprise-ai-skills --skill prioritizationgit clone --depth 1 https://github.com/sruthir28/enterprise-ai-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/sruthir28/enterprise-ai-skills/prioritization)<a href="https://agentmods.dev/skills/sruthir28/enterprise-ai-skills/prioritization"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/prioritization/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/sruthir28/enterprise-ai-skills/prioritization"><img src="https://agentmods.dev/badge/skills/sruthir28/enterprise-ai-skills/prioritization.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 | $0.00000 | $0.05221 |
| Opus 5.5 | $0.00000 | $0.02088 |
| Sonnet 5.5 | $0.00000 | $0.01044 |
| Haiku 4.5 | $0.00000 | $0.00522 |
Grade C, and why
prioritization scanned grade C with 1 finding 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 1mo 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.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
❌ **Never refuse to help due to missing data** - provide estimated ranges instead How it starts
The opening of the file, as written. The whole thing — 558 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Prioritization Framework
A comprehensive prioritization skill for product managers to evaluate features, initiatives, and tasks using proven frameworks.
Overview
This skill helps PMs make data-driven decisions by applying the right framework for their specific context. All outputs are provided in clean, tabular format for easy sharing with stakeholders.
When to Use This Skill
Use this skill when you need to:
- Prioritize a product roadmap
- Decide which features to build next
- Allocate team resources across initiatives
- Make tradeoff decisions between competing priorities
- Communicate priorities to stakeholders
Frameworks Included
1. RICE Scoring
When to use: When you have quantitative data and want an objective score
Best for: Feature prioritization, roadmap planning with multiple stakeholders
Requires: Estimates for reach, impact, confidence, and effort
Formula: (Reach × Impact × Confidence) / Effort
Components:
- Reach: How many users/customers affected in a time period
- Impact: Effect per person (Minimal=0.25, Low=0.5, Medium=1, High=2, Massive=3)
- Confidence: Estimate confidence (50%, 80%, 100%)
- Effort: Person-months required
Output Format:
| Feature | Reach | Impact | Confidence | Effort (PM) | RICE Score | Rank |
|---------|-------|--------|------------|-------------|------------|------|
| Feature A | 5000 | 2.0 | 100% | 3.0 | 3333 | 1 |
| Feature B | 3000 | 1.0 | 80% | 2.0 | 1200 | 2 |
2. Impact/Effort Matrix (2×2)
When to use: When you need quick visual prioritization or have limited data
Best for: Sprint planning, quick decisions, getting team alignment
Requires: Relative assessment of impact and effort (High/Low or Small/Medium/Large)
Quadrants:
- Quick Wins (High Impact, Low Effort) → Do First
- Big Bets (High Impact, High Effort) → Plan & Resource
- Fill-Ins (Low Impact, Low Effort) → Do When Available
- Money Pit (Low Impact, High Effort) → Avoid/Deprioritize
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 558 lines · 0 tokens per session scan C b66e108648cc
prioritization is a skill published in the GitHub repository sruthir28/enterprise-ai-skills (158 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 5,221 tokens. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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