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 majiayu000/spellbook --skill product-manager-toolkitgit clone --depth 1 https://github.com/majiayu000/spellbookWrote 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/majiayu000/spellbook/product-manager-toolkit)<a href="https://agentmods.dev/skills/majiayu000/spellbook/product-manager-toolkit"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/product-manager-toolkit/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/majiayu000/spellbook/product-manager-toolkit"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/product-manager-toolkit.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 | $0.00047 | $0.02137 |
| Opus 5.5 | $0.00019 | $0.00855 |
| Sonnet 5.5 | $0.00009 | $0.00427 |
| Haiku 4.5 | $0.00005 | $0.00214 |
Grade A, and why
product-manager-toolkit 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
2 near-identical copies found in the catalogue:
- product-manager-toolkit — 92% identical, 4 lines differ
- product-manager-toolkit — 88% identical, 15 lines differ
How it starts
The opening of the file, as written. The whole thing — 352 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Manager Toolkit Skill
Essential tools and frameworks for modern product management, from discovery to delivery.
Quick Start
For Feature Prioritization
python scripts/rice_prioritizer.py sample # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
For Interview Analysis
python scripts/customer_interview_analyzer.py interview_transcript.txt
For PRD Creation
- Choose template from
references/prd_templates.md - Fill in sections based on discovery work
- Review with stakeholders
- Version control in your PM tool
Core Workflows
Feature Prioritization Process
-
Gather Feature Requests
- Customer feedback
- Sales requests
- Technical debt
- Strategic initiatives
-
Score with RICE
# Create CSV with: name,reach,impact,confidence,effort python scripts/rice_prioritizer.py features.csv- Reach: Users affected per quarter
- Impact: massive/high/medium/low/minimal
- Confidence: high/medium/low
- Effort: xl/l/m/s/xs (person-months)
-
Analyze Portfolio
- Review quick wins vs big bets
- Check effort distribution
- Validate against strategy
-
Generate Roadmap
- Quarterly capacity planning
- Dependency mapping
- Stakeholder alignment
Customer Discovery Process
-
Conduct Interviews
- Use semi-structured format
- Focus on problems, not solutions
- Record with permission
-
Analyze Insights
python scripts/customer_interview_analyzer.py transcript.txtExtracts:
- Pain points with severity
- Feature requests with priority
- Jobs to be done
- Sentiment analysis
- Key themes and quotes
-
Synthesize Findings
- Group similar pain points
- Identify patterns across interviews
- Map to opportunity areas
-
Validate Solutions
- Create solution hypotheses
- Test with prototypes
- Measure actual vs expected behavior
What ships with it
3 files 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 · 352 lines · 47 tokens per session scan A ef0f490e401d
product-manager-toolkit is a skill published in the GitHub repository majiayu000/spellbook (288 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 2,137 once invoked, about $0.0002 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 2026-09-03.
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