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 bitovi/cascade-mcp --skill write-next-story-from-shell-storygit clone --depth 1 https://github.com/bitovi/cascade-mcpWrote 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/bitovi/cascade-mcp/write-next-story-from-shell-story)<a href="https://agentmods.dev/skills/bitovi/cascade-mcp/write-next-story-from-shell-story"><img src="https://agentmods.dev/badge/skills/bitovi/cascade-mcp/write-next-story-from-shell-story/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/bitovi/cascade-mcp/write-next-story-from-shell-story"><img src="https://agentmods.dev/badge/skills/bitovi/cascade-mcp/write-next-story-from-shell-story.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 | $0.00097 | $0.02773 |
| Opus 5 | $0.00048 | $0.01386 |
| Sonnet 5 | $0.00019 | $0.00555 |
| Haiku 4.5 | $0.00010 | $0.00277 |
Grade B, and why
write-next-story-from-shell-story scanned grade B with 2 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 12d 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -sL "{downloadUrl}" -o /tmp/cascade-figma.zip && unzip -qo /tmp/cascade-figma.zip -d .temp/cascade/figma/ && rm /tmp/cascade-figma.zip Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sL "{downloadUrl}" -o /tmp/cascade-figma.zip && unzip -qo /tmp/cascade-figma.zip -d .temp/cascade/figma/ && rm /tmp/cascade-figma.zip How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Next Story From Shell Story
Turn the next unwritten shell story in a Jira epic into a full Jira subtask with comprehensive acceptance criteria, by loading only the relevant Figma screens and using the shell story's scope bullets as the scope anchor.
When to Use
Use when the user wants to:
- Write out the next shell story in an epic as a full Jira story
- Turn a specific shell story into a full ticket
- Continue advancing an epic story by story after shell stories have been generated
Typical triggers:
- "Write the next story from PROJ-123's shell stories"
- "Write st003 from PROJ-123"
- "Advance the epic PROJ-123 — write the next story"
Required Input
- Jira epic key (e.g.,
PROJ-123) — the epic containing the shell stories - Specific story ID (optional, e.g.,
st003) — if omitted, the first unwritten story is used
Procedure
Phase 1: Fetch the Epic
Call MCP tool extract-linked-resources with the Jira epic URL (e.g., https://myco.atlassian.net/browse/PROJ-123).
Save the returned markdown+frontmatter directly to .temp/cascade/context/jira-PROJ-123.md.
Parse discoveredLinks from frontmatter to build .temp/cascade/context/to-load.md.
Phase 2: Iterative Content Loading
For each non-Figma URL in to-load.md (prioritize parent and blocks relationships first):
- Call
extract-linked-resourceswith the URL - Save the returned markdown to
.temp/cascade/context/{type}-{identifier}.md - Parse
discoveredLinksfrom frontmatter — add any new URLs toto-load.md - Repeat until no unloaded non-Figma URLs remain
Important: Figma URLs are collected but NOT loaded here — only the target shell story's screens will be loaded in Phase 3.
Phase 3: Identify Target Shell Story
Read the current epic description via atlassian-get-issue and locate the ## Shell Stories section.
Parse shell stories from the section. Find the target story:
- If a specific story ID was provided (e.g.,
st003), use that story - Otherwise, use the first story without a completion marker (i.e., the title is plain text, not a Jira link with a timestamp)
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.
- 12d ago First seen · 218 lines · 97 tokens per session scan B 7e3e5fc7aa27
write-next-story-from-shell-story is a skill published in the GitHub repository bitovi/cascade-mcp (24 stars, last pushed 22d ago), licensed MIT. It adds 97 tokens to every session and 2,773 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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