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 cwinvestments/memstack --skill user-story-generatorgit clone --depth 1 https://github.com/cwinvestments/memstackWrote 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/cwinvestments/memstack/user-story-generator)<a href="https://agentmods.dev/skills/cwinvestments/memstack/user-story-generator"><img src="https://agentmods.dev/badge/skills/cwinvestments/memstack/user-story-generator/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/cwinvestments/memstack/user-story-generator"><img src="https://agentmods.dev/badge/skills/cwinvestments/memstack/user-story-generator.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 | $0.00064 | $0.02429 |
| Opus 5.5 | $0.00026 | $0.00972 |
| Sonnet 5.5 | $0.00013 | $0.00486 |
| Haiku 4.5 | $0.00006 | $0.00243 |
Grade A, and why
memstack-product-user-story-generator 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.
How it starts
The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Story Generator: Generating user stories...
Produces prioritized user stories with Given/When/Then acceptance criteria, story point estimates, story mapping across epics, and MoSCoW prioritization for sprint planning.
Activation
When this skill activates, output:
User Story Generator: Generating user stories...
Then execute the protocol below.
Context Guard
| Context | Status |
|---|---|
| User says "user stories", "write stories", "backlog" | ACTIVE |
| User says "sprint planning" or "acceptance criteria" | ACTIVE |
| User wants to break work into estimable, assignable stories | ACTIVE |
| User wants a full product requirements document | DORMANT: use PRD Writer |
| User wants a detailed spec for one feature | DORMANT: use Feature Spec |
Common Mistakes
| Mistake | Why It's Wrong |
|---|---|
| "As a user, I want the system to..." | Stories describe user needs, not system behavior. The "I want to" should be a user action. |
| "Write a story for every edge case" | Edge cases go in acceptance criteria, not separate stories. One story per user intent. |
| "Stories without acceptance criteria" | "Done" becomes subjective. Every story needs testable criteria before sprint planning. |
| "Estimate in hours" | Hours vary by person. Story points measure relative complexity, not calendar time. |
| "50-point stories in the sprint" | If it's bigger than 8 points, split it. Large stories hide unknowns and block the team. |
Protocol
Step 1: Gather Context
If the user hasn't provided details, ask:
- Feature/epic: what area are you writing stories for?
- Personas: who are the users? (roles, permissions, experience levels)
- Existing context: is there a PRD, feature spec, or design to reference?
- Sprint goal: what are you trying to ship this sprint?
- Team capacity: how many story points can the team handle? (helps scope)
Step 2: Identify Epics & Themes
Group stories under epics (large bodies of work):
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 Changed 6ee3d7124bb2
- 1mo ago First seen · 293 lines · 64 tokens per session scan A 1d8d5db5ef57
memstack-product-user-story-generator is a skill published in the GitHub repository cwinvestments/memstack (425 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 2,429 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 2026-09-03.
Other skills, from other repositories
ccpm
CCPM - spec-driven project management: PRD → Epic → GitHub Issues → parallel agents → shipped code. Use this skill for anything in the software delivery lifecycle: writing a PRD ('write a PRD for X', 'let's plan X', 'scope this out'), parsing a PRD into an epic, decomposing an epic into tasks, syncing to GitHub ('sync…
github-workflow
GitHub best practices for pull requests, code reviews, issues, Actions workflows, and repository management.
lerna
Best practices for Lerna monorepo management, versioning, and publishing.
issue-triage
3-phase issue backlog management with audit, deep analysis, and validated triage actions. Use when triaging GitHub issues, sorting bug reports, cleaning up stale tickets, or detecting duplicate issues. Args: 'all' to analyze all, issue numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit only.
customer-success
Support workflows, ticketing systems (Zendesk, Intercom), knowledge base design, chatbot design, and metrics (CSAT, NPS). Use when building support infrastructure, designing help centers, or optimizing customer experience.
event-planner
Event planning with timelines, budgets, vendor coordination, logistics checklists, and post-event evaluation. Use when organizing conferences, workshops, galas, or corporate events.