This skill uses internal agent modes for type-specific drafting logic:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfusion-issue-authoringExecute the skills CLI command in your project's root directory to begin installation:
Fetches fusion-issue-authoring from equinor/fusion-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate fusion-issue-authoring. Access via /fusion-issue-authoring in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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This skill uses internal agent modes for type-specific drafting logic:
agents/bug.agent.md: bug-focused issue drafting and triage structureagents/feature.agent.md: feature-focused scope and acceptance structureagents/user-story.agent.md: role/workflow/scenario-driven story structureagents/task.agent.md: checklist-first task decomposition and dependency planningagents/devils-advocate.agent.md: always-on quality collaborator that raises key concerns after classification (moderate mode) and runs a full structured interview when explicitly asked or when scope/criteria gaps are significant (interrogator mode)Agent modes are activated internally based on issue type classification. Users never reference agent files directly. Shared gates (labels, assignee confirmation, draft review, publish confirmation, and mutation sequencing) remain in this skill.
Use this skill when you need to turn ideas, bugs, feature requests, or user needs into clear, actionable GitHub issues. Use it as the top-level router for both creating and updating issues.
Typical triggers:
Do not use this skill for:
Collect before publishing:
.tmp/ cache file that is never committed.@me or an exact login.If required details are missing, ask concise clarifying questions from references/questions.md.
If issue destination is unclear, ask explicitly where the issue should be created/updated before drafting mutation commands.
Classify request as Bug, Feature, User Story, or Task, then activate the matching agent mode:
agents/bug.agent.mdagents/feature.agent.mdagents/user-story.agent.mdagents/task.agent.mdIf ambiguous, ask only essential clarifying questions.
Devil's advocate pass: agents/devils-advocate.agent.md is always active in moderate mode — it surfaces the 2–3 most important concerns after classification without interrupting flow. When the user asks to be "grilled", says "stress-test this", or when scope/criteria gaps are significant, escalate to interrogator mode for a full structured interview before the type-specific agent. The devil's advocate returns confirmed decisions and noted risks, then hands off to the type-specific drafting agent.
CONTRIBUTING.md, contribute/) that define default issue routing by type. Apply any routing rules found there before asking the user..github/ISSUE_TEMPLATE/)Run one focused duplicate search with mcp_github::search_issues and surface matches before drafting/publishing.
Do not run repeated broad duplicate scans unless the user changes scope/title materially.
Before writing, check user preferences and session memory for a preferred draft location. If a stored preference exists, use it. If no preference is found and the intent is ambiguous, ask once and remember the answer for the session. Default to .tmp/{TYPE}-{CONTEXT}.md when no preference is found and there is nothing to ask about. Write the draft using GitHub Flavored Markdown.
Before mutation, confirm:
@me, specific login, or unassigned)Shared gate cache policy:
owner/repo, fetch the repository label set once and cache it for the active session. Prefer /memories/session/<owner>-<repo>-labels.json when the host exposes session memory; otherwise use .tmp/issue-authoring-labels-<owner>-<repo>.json.mcp_github::issue_write call and handle a single rejection path.mcp_github::search_users when the user already gave @me or an exact GitHub login./memories/session/<owner>-<repo>-assignee-candidates.json or /memories/session/<owner>-assignee-candidates.json; otherwise use .tmp/issue-authoring-assignee-candidates-<owner>-<repo>.json.After explicit confirmation, execute MCP mutations in this order:
mcp_github::issue_write create/update with the full known payload (title, body, and include labels, assignees, type only when supported)mcp_github::issue_write only when required fields were unknown in step 1 and become available latermcp_github::sub_issue_write only when relationship/order changes are requestedmcp_github::add_issue_comment only when blocker/status notes are explicitly requestedIf mutation fails due to missing MCP server/auth/config:
references/mcp-server.mdRate-limit behavior:
API rate limit exceeded, secondary rate limit, GraphQL quota exhaustion).gh api/GraphQL retries when equivalent MCP capability exists.retry-after and x-ratelimit-reset headers before retrying any request.type rule:
type if the repository has issue types configured.mcp_github::list_issue_types only on cache miss or invalid cache.type for the rest of the session.Before linking:
Use detailed behavior and payload examples in references/instructions.md and references/mcp-server.md.
Use detailed authoring guidance in references/instructions.md.
Fallback template locations:
assets/issue-templates/bug.mdassets/issue-templates/feature.mdassets/issue-templates/user-story.mdassets/issue-templates/task*.md.tmp/Awaiting user content approval before any publish/update commandNever:
mcp_github::issue_write create/update without explicit user confirmationAlways:
owner/repo#123)fixes owner/repo#123, resolves owner/repo#123, or closes owner/repo#123)Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Solid pick for teams standardizing on skills: fusion-issue-authoring is focused, and the summary matches what you get after install.
fusion-issue-authoring is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
fusion-issue-authoring fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
fusion-issue-authoring reduced setup friction for our internal harness; good balance of opinion and flexibility.
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend fusion-issue-authoring for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: fusion-issue-authoring is the kind of skill you can hand to a new teammate without a long onboarding doc.
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for fusion-issue-authoring matched our evaluation — installs cleanly and behaves as described in the markdown.
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