fusion-issue-authoring▌
equinor/fusion-skills · updated Apr 8, 2026
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This skill uses internal agent modes for type-specific drafting logic:
Issue Authoring
Agent modes
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.
When to use
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:
- "create an issue"
- "draft a ticket"
- "turn this into a GitHub issue"
- "help me structure this work item"
- "update this issue"
- "maintain/clean up this issue"
When not to use
Do not use this skill for:
- Implementing code changes
- Pull request authoring or review
- General research tasks not resulting in an issue draft
- Mutating GitHub state without explicit user confirmation
Required inputs
Collect before publishing:
- Target repository for issue creation/update
- Issue intent/context
- Issue type (Bug, Feature, User Story, Task)
- Existing issue number/url when updating
- Repository label set (or confirmation that labels are intentionally skipped). Cache the full label set per repository for the active session and filter locally instead of validating labels one by one. Prefer host session memory when available; otherwise use a
.tmp/cache file that is never committed. - Parent/related issue links and dependency direction (sub-issue vs blocking)
- Assignee preference (assign to user, specific person, or leave unassigned). Reuse cached assignee-candidate results for the active session and skip candidate searches when the user already gave
@meor 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.
Instructions
Step 1 — Classify and route
Classify request as Bug, Feature, User Story, or Task, then activate the matching agent mode:
- Bug ->
agents/bug.agent.md - Feature ->
agents/feature.agent.md - User Story ->
agents/user-story.agent.md - Task ->
agents/task.agent.md
If 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.
Step 2 — Resolve repository and template
- Resolve the destination repository before any mutation.
- When no explicit repository is given, check the active workspace for contributor guides (
CONTRIBUTING.md,contribute/) that define default issue routing by type. Apply any routing rules found there before asking the user. - If no routing guidance exists in the repo, ask explicitly where the issue should be created.
- Template precedence:
- repository template (
.github/ISSUE_TEMPLATE/) - specialist fallback template
- repository template (
Step 3 — Check duplicates
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.
Step 4 — Draft first
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.
Step 5 — Review and confirm
- Ask for content edits first.
- Ask explicit publish confirmation before mutation.
- Never publish/update in the same pass as first draft unless user explicitly confirms.
Step 6 — Apply shared gates
Before mutation, confirm:
- labels (only labels that exist in the target repo)
- assignee intent (
@me, specific login, or unassigned)
Shared gate cache policy:
- On the first label lookup for
owner/repo, fetch the repository label set once and cache it for the active session. Prefer/memories/session/<owner>-<repo>-labels.jsonwhen the host exposes session memory; otherwise use.tmp/issue-authoring-labels-<owner>-<repo>.json. - On cache hit, validate requested labels locally. Do not repeat point lookups for each requested label.
- If the host only exposes point label lookups and no cached label set exists yet, do not loop through labels one by one. Ask whether to skip optional labels or include only user-confirmed labels in the first
mcp_github::issue_writecall and handle a single rejection path. - Skip
mcp_github::search_userswhen the user already gave@meor an exact GitHub login. - When assignee lookup is needed, cache candidate results for the active session keyed by owner/repo (or owner) and query. Prefer
/memories/session/<owner>-<repo>-assignee-candidates.jsonor/memories/session/<owner>-assignee-candidates.json; otherwise use.tmp/issue-authoring-assignee-candidates-<owner>-<repo>.json. - If rate limits block optional label or assignee enrichment, ask whether to continue without them instead of looping retries.
Step 7 — Mutate via MCP (ordered)
After explicit confirmation, execute MCP mutations in this order:
mcp_github::issue_writecreate/update with the full known payload (title,body, and includelabels,assignees,typeonly when supported)- Optional single follow-up
mcp_github::issue_writeonly when required fields were unknown in step 1 and become available later mcp_github::sub_issue_writeonly when relationship/order changes are requestedmcp_github::add_issue_commentonly when blocker/status notes are explicitly requested
If mutation fails due to missing MCP server/auth/config:
- explain the failure clearly
- guide user to setup steps in
references/mcp-server.md - retry after user confirms setup is complete
Rate-limit behavior:
- Detect and report rate-limit failures clearly (
API rate limit exceeded,secondary rate limit, GraphQL quota exhaustion). - Stop non-essential lookups and skip optional enrichments when rate limits are hit.
- Keep draft artifacts and return a safe retry plan instead of looping retries.
- Prefer MCP tools over ad hoc
gh api/GraphQL retries when equivalent MCP capability exists. - When using GraphQL fallback: mutations cost 5 secondary-limit points each (vs 1 for queries), so batch fields into a single mutation call and pause at least 1 second between mutation calls.
- Respect
retry-afterandx-ratelimit-resetheaders before retrying any request.
type rule:
- Only use
typeif the repository has issue types configured. - Use cached issue types per organization when available.
- Call
mcp_github::list_issue_typesonly on cache miss or invalid cache. - If issue types are not supported, omit
typefor the rest of the session.
Step 8 — Validate relationships
Before linking:
- use sub-issues for decomposition
- use sub-issue ordering to represent prerequisites
- ensure no contradictory dependency graph
Use detailed behavior and payload examples in references/instructions.md and references/mcp-server.md.
Core behavior to preserve
- Classification-first workflow
- Route-to-agent-mode workflow
- Draft-first workflow
- Clarifying questions for missing critical context
- Explicit confirmation before any GitHub mutation
Use detailed authoring guidance in references/instructions.md.
Fallback template locations:
- Bug:
assets/issue-templates/bug.md - Feature:
assets/issue-templates/feature.md - User Story:
assets/issue-templates/user-story.md - Task:
assets/issue-templates/task*.md
Expected output
- Selected agent mode path
- Draft issue file path under
.tmp/ - Template source used (repository template path or fallback asset path)
- Proposed title, body summary, and labels
- Issue type plan
- Dependency plan (order + proposed sub-issue/blocking links)
- Assignee plan (who will be assigned, or explicit unassigned decision)
- Explicit status:
Awaiting user content approvalbefore any publish/update command - Any related/duplicate issue links found
- Exact create/update command(s) to be run after confirmation
- Created/updated issue URL/number only after confirmed mutation
- Suggested template maintenance follow-up when repository templates are missing or weak
Safety & constraints
Never:
- Run
mcp_github::issue_writecreate/update without explicit user confirmation - Publish/update an issue before the user confirms the draft content is correct
- Assume the user wants to publish to GitHub
- Request or expose secrets/credentials
- Perform destructive commands without explicit confirmation
Always:
- Keep drafts concise and editable
- Prefer WHAT/WHY over implementation HOW in issue text
- Use full repository issue references (for example
owner/repo#123) - Use issue-closing keywords when closure is intended (for example
fixes owner/repo#123,resolves owner/repo#123, orcloses owner/repo#123)
How to use fusion-issue-authoring on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add fusion-issue-authoring
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches fusion-issue-authoring from GitHub repository equinor/fusion-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate fusion-issue-authoring. Access the skill through slash commands (e.g., /fusion-issue-authoring) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★53 reviews- ★★★★★Maya Patel· Dec 20, 2024
Solid pick for teams standardizing on skills: fusion-issue-authoring is focused, and the summary matches what you get after install.
- ★★★★★Sofia Anderson· Dec 20, 2024
fusion-issue-authoring is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chen Garcia· Dec 16, 2024
fusion-issue-authoring fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Li Anderson· Dec 16, 2024
fusion-issue-authoring reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Dec 12, 2024
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Benjamin Tandon· Dec 12, 2024
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Isabella Sharma· Dec 4, 2024
I recommend fusion-issue-authoring for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Amina Torres· Nov 23, 2024
Keeps context tight: fusion-issue-authoring is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Maya Tandon· Nov 11, 2024
fusion-issue-authoring has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sofia Diallo· Nov 7, 2024
Registry listing for fusion-issue-authoring matched our evaluation — installs cleanly and behaves as described in the markdown.
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