Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Check agent_mode in 00-inbox/MY-PROFILE.md frontmatter:
agent_mode: team — use parallel agents to check for duplicates across all active trackers simultaneously, then create the storyagent_mode: solo — check duplicates and create the story sequentially in the main conversation/create-user-storyRead 00-inbox/MY-INTEGRATIONS.md to determine which project trackers are active:
gh CLIjira CLI or Jira API via WebFetch04-projects/[project]/stories/ and inform the userRead 00-inbox/MY-PROFILE.md to get:
Ask the user (if not already provided):
Parse the user's input to extract:
If the user provides a brief description, ask clarifying questions before proceeding:
CRITICAL: Always check for duplicates before creating.
Launch duplicate-check agents in parallel using the Task tool with run_in_background: true:
Agent: "duplicate-checker-linear" (if Linear is active)
Search Linear for potential duplicate issues.
1. Use ToolSearch to load Linear tools
2. Use mcp__claude_ai_Linear_2__list_issues to search for issues with similar keywords
3. Search across all active projects/teams
4. Return any issues that match by title similarity or description overlap
Search terms: [extracted keywords from user's description]
Return: list of potential duplicates with title, status, URL, and similarity assessment
Agent: "duplicate-checker-github" (if GitHub is active)
Search GitHub Issues for potential duplicates.
Repository: [CUSTOMIZE: your-org/your-repo]
1. gh search issues "[keywords]" --repo [CUSTOMIZE: your-org/your-repo] --json number,title,state,url,body --limit 20
2. Also search closed issues to check if this was already done:
gh search issues "[keywords]" --repo [CUSTOMIZE: your-org/your-repo] --state closed --json number,title,state,url --limit 10
Return: list of potential duplicates with title, status, URL, and similarity assessment
Agent: "duplicate-checker-jira" (if Jira is active)
Search Jira for potential duplicate issues.
Project: [CUSTOMIZE: YOUR-PROJECT-KEY]
1. Use WebFetch or jira CLI to search:
JQL: project = "[CUSTOMIZE: YOUR-PROJECT-KEY]" AND text ~ "[keywords]" ORDER BY created DESC
2. Check both open and recently resolved issues
Return: list of potential duplicates with key, title, status, URL, and similarity assessment
Run the same duplicate checks sequentially for whichever tracker is active.
If potential duplicates are found, present them to the user:
I found [N] potential duplicate(s):
1. **[TITLE]** ([STATUS]) — [URL]
Similarity: [High/Medium/Low] — [reason]
2. **[TITLE]** ([STATUS]) — [URL]
Similarity: [High/Medium/Low] — [reason]
Options:
a) These are different — proceed with creating the new story
b) This is a duplicate of #[N] — skip creation
c) This is related to #[N] — create and link them
Wait for user confirmation before proceeding.
Generate the story in standard user story format:
## Title
[Concise, descriptive title]
## User Story
**As a** [type of user],
**I want** [goal/desire],
**So that** [benefit/value].
## Description
[Expanded description of the feature, including context and background]
## Acceptance Criteria
### Scenario 1: [Happy path scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]
### Scenario 2: [Alternative scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]
### Scenario 3: [Edge case or error scenario name]
- **Given** [precondition]
- **When** [action]
- **Then** [expected outcome]
## Technical Notes
[Any implementation hints, constraints, or dependencies — if applicable]
## Out of Scope
[What this story explicitly does NOT cover — helps prevent scope creep]
Present the formatted story to the user for review before creating it.
After user approves the story content:
1. Use ToolSearch to load Linear tools
2. Use mcp__claude_ai_Linear_2__get_team to find the target team
3. Use mcp__claude_ai_Linear_2__list_issue_labels to find appropriate labels
4. Use mcp__claude_ai_Linear_2__save_issue to create the issue with:
- title: [story title]
- description: [full story in markdown]
- team: [target team]
- priority: [user-specified or default medium]
- labels: [appropriate labels]
gh issue create \
--repo [CUSTOMIZE: your-org/your-repo] \
--title "[story title]" \
--body "[full story in markdown]" \
--label "[appropriate labels]"
Use WebFetch to POST to Jira REST API or use jira CLI:
- Project: [CUSTOMIZE: YOUR-PROJECT-KEY]
- Issue Type: Story
- Summary: [story title]
- Description: [full story in markdown/Jira wiki format]
- Priority: [user-specified or default Medium]
- Labels: [appropriate labels]
Save to 04-projects/[project]/stories/story-YYYY-MM-DD-[slug].md
Confirm creation with the user:
Story created: **[TITLE]**
[URL or file path]
Priority: [priority]
Labels: [labels]
If the user indicated this is related to another issue (Phase 3, option c), create a link/relation between them.
Also save a local copy to 04-projects/[project]/stories/ for vault reference.
| Scenario | Behavior |
|---|---|
| No tracker active | Save as markdown in 04-projects/[project]/stories/ |
| Tracker API fails | Save locally, warn user, suggest manual creation with the formatted content |
| Duplicate check fails | Warn user that duplicate check was skipped, proceed with creation after confirmation |
| User doesn't specify project | List active projects from MY-PROFILE.md and ask which one |
| User provides minimal input | Ask clarifying questions to build a complete story |
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概要と使いどころ
Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。