phuryn/pm-skills is a marketplace of reusable skills, commands, and plugins that guide AI assistants through product-management work such as discovery, strategy, planning, metrics, launches, and growth. It is for product managers and teams using Claude Code, Cowork, or compatible assistants. The catalogue entries are the project's own workflows and extensions.
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.
git clone --depth 1 https://github.com/phuryn/pm-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/commands/phuryn/pm-skills/test-scenarios)<a href="https://agentmods.dev/commands/phuryn/pm-skills/test-scenarios"><img src="https://agentmods.dev/badge/commands/phuryn/pm-skills/test-scenarios/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/commands/phuryn/pm-skills/test-scenarios"><img src="https://agentmods.dev/badge/commands/phuryn/pm-skills/test-scenarios.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 | $0.00020 | $0.00629 |
| Opus 5 | $0.00010 | $0.00315 |
| Sonnet 5 | $0.00004 | $0.00126 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
test-scenarios 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 10d 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:
- test-scenarios — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/test-scenarios -- Test Scenario Generator
Turn user stories or feature descriptions into comprehensive test scenarios that QA can execute immediately. Covers happy paths, edge cases, error handling, and cross-browser/device considerations.
Invocation
/test-scenarios [paste user stories or acceptance criteria]
/test-scenarios [upload a PRD or feature spec]
/test-scenarios User can reset their password via email link
Workflow
Step 1: Accept Input
Accept: user stories, acceptance criteria, PRD sections, feature descriptions, or any specification of expected behavior.
Step 2: Generate Test Scenarios
Apply the test-scenarios skill:
For each user story or requirement, generate:
Happy Path Scenarios: The expected user flow works correctly Edge Cases: Boundary conditions, unusual inputs, concurrent operations Error Scenarios: What happens when things go wrong Security Scenarios: If applicable (auth, permissions, data access) Performance Scenarios: If applicable (load, timeout, large data)
Step 3: Structure Output
## Test Scenarios: [Feature]
**Source**: [user stories / PRD / description]
**Total scenarios**: [count]
**Coverage**: [happy path / edge cases / errors / security / performance]
### Scenario 1: [Title]
**Tests**: [which story or requirement]
**Preconditions**: [setup needed]
**User role**: [who is performing this]
| Step | Action | Expected Result |
|------|--------|----------------|
| 1 | [user action] | [expected system response] |
| 2 | [user action] | [expected system response] |
**Postconditions**: [state after completion]
**Priority**: [Critical / High / Medium / Low]
---
[Repeat for each scenario]
### Coverage Matrix
| Requirement | Happy Path | Edge Cases | Error Handling | Notes |
|------------|-----------|-----------|---------------|-------|
### Test Data Requirements
[What test data is needed to execute these scenarios]
Save as markdown.
Step 4: Offer Next Steps
- "Want me to generate the test data for these scenarios?"
- "Should I add more edge cases for any specific scenario?"
- "Want me to create the user stories that these scenarios test?"
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.
- 10d ago First seen · 84 lines · 20 tokens per session scan A 426759788947
test-scenarios is a command published in the GitHub repository phuryn/pm-skills (26,131 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 629 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
experiment-ideas
Generate several concrete, brain-grounded growth ideas — channel, message, rationale, cost-efficiency — ranked by effort vs. impact.
value-prop-statements
Fan an existing positioning statement out into segment- and channel-specific value-prop copy variants, trace-checked against drift.
gtm-motions
Score and select a GTM motion stack against real deal economics, not a taxonomy tour.
buyer-personas
Map the buying committee, then build alternatives-anchored messaging personas.
ideal-customer-profile
Build, enrich, or audit your ICP — trigger events, buyer map, JTBD, disqualifiers.
positioning-messaging
Build or audit positioning statements, messaging, and related output.