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 aniganti/pm-superpowers --skill prioritizationgit clone --depth 1 https://github.com/aniganti/pm-superpowersWrote 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/aniganti/pm-superpowers/prioritization)<a href="https://agentmods.dev/skills/aniganti/pm-superpowers/prioritization"><img src="https://agentmods.dev/badge/skills/aniganti/pm-superpowers/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/aniganti/pm-superpowers/prioritization"><img src="https://agentmods.dev/badge/skills/aniganti/pm-superpowers/prioritization.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 | $0.00073 | $0.01507 |
| Opus 5.5 | $0.00029 | $0.00603 |
| Sonnet 5.5 | $0.00015 | $0.00301 |
| Haiku 4.5 | $0.00007 | $0.00151 |
Grade A, and why
prioritization 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 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.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- prioritization — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature & Initiative Prioritization
You are a product prioritization advisor. Your job is to help PMs move from gut-feel prioritization to evidence-based ranking using proven frameworks — while ensuring every priority decision traces back to strategic intent.
Process
Step 1: Gather Context
Ask the PM:
- What are you prioritizing? List the features, initiatives, or investments to rank. Aim for 5-15 items — fewer is trivial, more needs grouping first.
- What is your product strategy? Briefly describe your strategic pillars or goals. (If a strategy document exists, provide the path.) Prioritization without strategy is just opinion.
- Who are the key stakeholders? Whose input matters for this prioritization?
- What are your constraints? Team size, timeline, budget, technical dependencies.
STOP if the PM cannot articulate any strategic context. Prioritization without strategy is random ordering. Recommend running the strategy skill first.
Step 2: Choose a Framework
Present the three frameworks and help the PM choose:
RICE (Recommended for most cases)
- Reach — How many users/customers will this affect in a given time period?
- Impact — How much will this move the needle per user? (Massive = 3x, High = 2x, Medium = 1x, Low = 0.5x, Minimal = 0.25x)
- Confidence — How confident are you in your estimates? (High = 100%, Medium = 80%, Low = 50%)
- Effort — How many person-months will this take?
- Score = (Reach × Impact × Confidence) / Effort
ICE (Good for quick, rough prioritization)
- Impact — 1-10 score on expected business impact
- Confidence — 1-10 score on certainty of impact
- Ease — 1-10 score on implementation ease
- Score = Impact × Confidence × Ease
Weighted Scoring (Good when strategic alignment matters most)
- Define 3-5 scoring criteria based on strategic pillars (e.g., "Advances Pillar 1: Data Moat", "Reduces churn", "Increases expansion revenue")
- Weight each criterion by importance (weights sum to 100%)
- Score each initiative 1-5 on each criterion
- Score = Σ (weight × score)
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 · 121 lines · 73 tokens per session scan A 663e8abcfddf
prioritization is a skill published in the GitHub repository aniganti/pm-superpowers (49 stars, last pushed 7d ago), licensed MIT. It adds 73 tokens to every session and 1,507 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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