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 hieptran87/atlassian-mcp-server --skill spec-to-backloggit clone --depth 1 https://github.com/hieptran87/atlassian-mcp-serverWrote 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/hieptran87/atlassian-mcp-server/spec-to-backlog)<a href="https://agentmods.dev/skills/hieptran87/atlassian-mcp-server/spec-to-backlog"><img src="https://agentmods.dev/badge/skills/hieptran87/atlassian-mcp-server/spec-to-backlog/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/hieptran87/atlassian-mcp-server/spec-to-backlog"><img src="https://agentmods.dev/badge/skills/hieptran87/atlassian-mcp-server/spec-to-backlog.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 | $0.00098 | $0.04002 |
| Opus 5 | $0.00049 | $0.02001 |
| Sonnet 5 | $0.00020 | $0.00800 |
| Haiku 4.5 | $0.00010 | $0.00400 |
Grade A, and why
spec-to-backlog 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 11d 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.
This is a copy
86% identical to spec-to-backlog — 146 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 540 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec to Backlog
Overview
Transform Confluence specification documents into structured Jira backlogs automatically. This skill reads requirement documents from Confluence, intelligently breaks them down into logical implementation tasks, creates an Epic first to organize the work, then generates individual Jira tickets linked to that Epic—eliminating tedious manual copy-pasting.
Core Workflow
CRITICAL: Always follow this exact sequence:
- Fetch Confluence Page → Get the specification content
- Ask for Project Key → Identify target Jira project
- Analyze Specification → Break down into logical tasks (internally, don't create yet)
- Present Breakdown → Show user the planned Epic and tickets
- Create Epic FIRST → Establish parent Epic and capture its key
- Create Child Tickets → Generate tickets linked to the Epic
- Provide Summary → Present all created items with links
Why Epic must be created first: Child tickets need the Epic key to link properly during creation. Creating tickets first will result in orphaned tickets.
Step 1: Fetch Confluence Page
When triggered, obtain the Confluence page content:
If user provides a Confluence URL:
Extract the page ID from the URL pattern:
- Standard format:
https://[site].atlassian.net/wiki/spaces/[SPACE]/pages/[PAGE_ID]/[title] - The page ID is the numeric value in the URL path
If user provides only a page title or description:
Use the confluence_search tool to find the page:
confluence_search(
cql="type=page AND title~'[search terms]'"
)
If multiple pages match, ask the user to clarify which one to use.
Fetch the page:
Call confluence_get_page with the pageId:
confluence_get_page(
page_id="123456"
)
This returns the page content in Markdown format, which you'll analyze in Step 3.
Step 2: Ask for Project Key
Before analyzing the spec, determine the target Jira project:
Ask the user:
"Which Jira project should I create these tickets in? Please provide the project key (e.g., PROJ, ENG, PRODUCT)."
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.
- 11d ago First seen · 540 lines · 98 tokens per session scan A 02da938b0f29
spec-to-backlog is a skill published in the GitHub repository hieptran87/atlassian-mcp-server (0 stars, last pushed 1mo ago), licensed MIT. It adds 98 tokens to every session and 4,002 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to spec-to-backlog, differing in 146 lines, and is treated as a copy.
Other skills, from other repositories
recipe-create-doc-from-template
Copy a Google Docs template, fill in content, and share with collaborators.
reversa-sync
Convergência pós-coding do Reversa: destila a feature entregue num adendo em reversasdd/addenda/, mantendo a extração representativa entre re-extrações, sem tocar nos artefatos originais. Passo opcional do ciclo forward após /reversa-coding.
sred-project-organizer
Take a list of projects and their related documentation, and organize them into the SRED format for submission.
notion
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
slack-report-delivery
Deliver formatted network reports, audit results, topology diagrams, and compliance documentation to Slack channels with rich Block Kit formatting. Use when posting a health check report, sharing a security audit, delivering topology diagrams, or sending scheduled network reports to Slack.
notion
Search, read, create, and update Notion pages and databases. Supports knowledge capture, meeting prep, research documentation, and spec-to-task workflows.