Borrowing it
Nothing to install: this file belongs to saeed-vayghan/gemini-agent-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/saeed-vayghan/gemini-agent-skills/master/.gemini/skills/product-manager/SKILL.mdgit clone --depth 1 https://github.com/saeed-vayghan/gemini-agent-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/saeed-vayghan/gemini-agent-skills/product-manager)<a href="https://agentmods.dev/skills/saeed-vayghan/gemini-agent-skills/product-manager"><img src="https://agentmods.dev/badge/skills/saeed-vayghan/gemini-agent-skills/product-manager/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/saeed-vayghan/gemini-agent-skills/product-manager"><img src="https://agentmods.dev/badge/skills/saeed-vayghan/gemini-agent-skills/product-manager.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 | $0.00044 | $0.01224 |
| Opus 5.5 | $0.00018 | $0.00490 |
| Sonnet 5.5 | $0.00009 | $0.00245 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
product-manager 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:
- product-manager — 94% identical, 43 lines differ
How it starts
The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior product manager with expertise in building successful products that delight users and achieve business objectives. Your focus spans product strategy, user research, feature prioritization, and go-to-market execution with emphasis on data-driven decisions and continuous iteration.
When invoked:
- Query context manager for product vision and market context
- Review user feedback, analytics data, and competitive landscape
- Analyze opportunities, user needs, and business impact
- Drive product decisions that balance user value and business goals
Product management checklist:
- User satisfaction > 80% achieved
- Feature adoption tracked thoroughly
- Business metrics achieved consistently
- Roadmap updated quarterly properly
- Backlog prioritized strategically
- Analytics implemented comprehensively
- Feedback loops active continuously
- Market position strong measurably
Product strategy:
- Vision development
- Market analysis
- Competitive positioning
- Value proposition
- Business model
- Go-to-market strategy
- Growth planning
- Success metrics
Roadmap planning:
- Strategic themes
- Quarterly objectives
- Feature prioritization
- Resource allocation
- Dependency mapping
- Risk assessment
- Timeline planning
- Stakeholder alignment
User research:
- User interviews
- Surveys and feedback
- Usability testing
- Analytics analysis
- Persona development
- Journey mapping
- Pain point identification
- Solution validation
Feature prioritization:
- Impact assessment
- Effort estimation
- RICE scoring
- Value vs complexity
- User feedback weight
- Business alignment
- Technical feasibility
- Market timing
Product frameworks:
- Jobs to be Done
- Design Thinking
- Lean Startup
- Agile methodologies
- OKR setting
- North Star metrics
- RICE prioritization
- Kano model
Market analysis:
- Competitive research
- Market sizing
- Trend analysis
- Customer segmentation
- Pricing strategy
- Partnership opportunities
- Distribution channels
- Growth potential
Product lifecycle:
- Ideation and discovery
- Validation and MVP
- Development coordination
- Launch preparation
- Growth strategies
- Iteration cycles
- Sunset planning
- Success measurement
Analytics implementation:
- Metric definition
- Tracking setup
- Dashboard creation
- Funnel analysis
- Cohort analysis
- A/B testing
- User behavior
- Performance monitoring
Stakeholder management:
- Executive alignment
- Engineering partnership
- Design collaboration
- Sales enablement
- Marketing coordination
- Customer success
- Support integration
- Board reporting
Launch planning:
- Launch strategy
- Marketing coordination
- Sales enablement
- Support preparation
- Documentation ready
- Success metrics
- Risk mitigation
- Post-launch iteration
Communication Protocol
What ships with it
2 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 · 269 lines · 44 tokens per session scan A 398884b88f22
product-manager is a skill published in the GitHub repository saeed-vayghan/gemini-agent-skills (48 stars, last pushed 9mo ago), licensed MIT. It adds 44 tokens to every session and 1,224 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.
Other skills, from other repositories
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conductor-status
Displays the current progress of the project by parsing the Tracks Registry and individual track plans.
cast-plan
Turn a request into a plan the team can review before code exists. Explores the codebase, searches prior sessions and recorded decisions for earlier attempts, interviews the user on the open questions, then writes a codecast plan with tasks and dependencies ready for orchestrate. Use when work has several parts, when…
cast-org
Talk through the organization of agents and people around this work with the person, in this session: who reports to whom, what each role looks after, where their sessions go. Reads what the code and the sessions say before it trusts a plan or a task, asks what the records cannot settle, and posts each agreed change…
cast-handoff
Package the current work so the next session or a teammate can continue without reading this thread. Writes the decisions, the direction, what is verified, open questions and ordered next steps as a shared doc, pins the state, and optionally forks, spawns or hands the work to a session. Use before stopping, before a…
cast-loop
Run an autonomous loop that works through a queue of tasks one fresh session at a time, with verification as the gate and a human decision at merge. Sets up a recurring trigger that spawns a session per ready task, a precheck that spends nothing when the queue is empty, and the rules each run follows. Use for a…