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linear-agent

@mberto10/web_research_agent
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Intelligent, conversational interface for managing Linear workspace operations (issues, projects, teams, reporting)

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SKILL.md

name linear-agent
description Intelligent, conversational interface for managing Linear workspace operations (issues, projects, teams, reporting)
allowed-tools *

Linear Agent Skill

Purpose

Intelligent, conversational interface for managing Linear workspace operations. This skill provides comprehensive issue management, project planning, team coordination, and reporting capabilities through natural language interaction.

Core Capabilities:

  • Issue Management: Create, retrieve, update, and search issues with smart defaults
  • Project Planning: Bulk operations for epics, milestones, and feature sets
  • Team Coordination: Assign work, track progress, manage workloads
  • Reporting: Generate team summaries, sprint reports, and activity metrics
  • Templates: Pre-configured patterns for bugs, features, and tasks

Architecture

This skill wraps the MCP Linear tools and provides helper utilities that add:

  • Retry logic and error handling
  • Smart defaults and validation
  • Template-based issue creation
  • Batch operations
  • Natural language → Linear API translation

Helper Scripts:

  • linear_client.py: Unified API client with retry logic
  • create_issue.py: Template-based issue creation
  • update_issue.py: Issue updates with validation
  • query_issues.py: Advanced querying and filtering
  • bulk_operations.py: Batch create/update operations
  • reporting.py: Team and sprint reports

Templates:

  • bug_report.yaml: Bug issue template
  • feature_request.yaml: Feature request template
  • task.yaml: Generic task template

Workflows

Workflow 1: Create Issue

Trigger: User wants to create a new Linear issue

Steps:

  1. Understand Requirements

    • Extract issue details from user's natural language request
    • Identify: title, description, type (bug/feature/task), priority, labels
    • Ask clarifying questions if needed

  2. Select Team

    • If team not specified, list available teams using linear_client.py
    • Ask user to select team or infer from context

  3. Choose Template (Optional)

    • For bugs: Use bug_report.yaml template
    • For features: Use feature_request.yaml template
    • For tasks: Use task.yaml template
    • For simple issues: Skip template

  4. Populate Fields

    • If using template, gather template variables
    • Apply smart defaults:
      • Priority: 3 (Normal) unless specified
      • Labels: Infer from issue type and content
      • Estimate: Leave empty unless specified

  5. Create Issue

    • Use helpers/create_issue.py with gathered information
    • Example:
      python helpers/create_issue.py \
  --team "Backend Team" \
  --title "Fix authentication timeout" \
  --description "Users report 30s timeout on login" \
  --labels "bug,p1" \
  --priority 2 \
  --verbose

  6. Return Results

    • Show created issue ID, title, and URL
    • Confirm status and next steps

Example Interaction:

User: "Create a bug issue for authentication timeout in the backend team"
Skill: "I'll create a bug issue for the Backend Team. Let me gather some details:
  - What steps reproduce the issue?
  - What's the expected vs actual behavior?
  - What environment (OS, version)?"
User: "Login page → 30s timeout. Should login in <3s. Chrome on Mac."
Skill: *Creates issue using bug template with details*
Result: "✅ Created ISS-456: [BUG] Authentication timeout - https://linear.app/..."

Workflow 2: Query & Retrieve Issues

Trigger: User wants to find or list issues with specific criteria

Steps:

  1. Parse Query

    • Extract filters: team, state, assignee, priority, labels, keywords
    • Identify search mode: list all, filter by criteria, search by keyword

  2. Execute Query

    • Use helpers/query_issues.py with parsed filters
    • Example:
      python helpers/query_issues.py \
  --team "Backend Team" \
  --state "In Progress" \
  --labels "bug" \
  --verbose

  3. Format Results

    • For small result sets (<10): Show full details
    • For larger sets: Show summary table with ID, title, state, priority
    • Offer to export as CSV/JSON if many results

  4. Follow-up Actions

    • Ask if user wants to update any of the found issues
    • Offer to generate report from results

Example Interaction:

User: "Show me all in-progress bugs for the backend team"
Skill: *Executes query with filters*
Result: "Found 8 in-progress bugs:
  ISS-123: Login timeout
  ISS-124: API rate limit error
  ...
  Would you like to update any of these?"

Workflow 3: Update Issue

Trigger: User wants to modify an existing issue

Steps:

  1. Identify Issue

    • Get issue ID from user (e.g., "ISS-123")
    • OR find issue by title/description if ID not provided

  2. Fetch Current State

    • Retrieve current issue using linear_client.py
    • Show current values for fields being updated

  3. Determine Updates

    • Extract fields to update from user request
    • Supported: title, description, priority, state, assignee, labels, estimate

  4. Apply Updates

    • Use helpers/update_issue.py with changes
    • Example:
      python helpers/update_issue.py \
  --issue-id ISS-123 \
  --state "In Progress" \
  --assignee "user_abc123" \
  --comment "Starting work on this" \
  --verbose

  5. Confirm Changes

    • Show before/after snapshot
    • Display updated issue URL

Example Interaction:

User: "Move ISS-123 to In Progress and assign to me"
Skill: *Fetches current state, applies updates*
Result: "✅ Updated ISS-123:
  State: Backlog → In Progress
  Assignee: Unassigned → John Doe
  Added comment explaining changes"

Workflow 4: Bulk Operations

Trigger: User wants to create/update multiple issues at once

Steps:

  1. Understand Scope

    • Determine operation type: create or update
    • Identify source: YAML file, CSV, or manual list

  2. Prepare Batch File (if needed)

    • If user provides data directly, create temporary batch file
    • Format:
      team: "Backend Team"
issues:
  - title: "Issue 1"
    description: "Description 1"
    labels: ["bug", "p1"]
  - title: "Issue 2"
    priority: 2

  3. Validate Batch

    • Check all required fields present
    • Warn about missing optional fields
    • Confirm with user before executing

  4. Execute Batch

    • Use helpers/bulk_operations.py
    • Show progress for each issue
    • Example:
      python helpers/bulk_operations.py \
  --action create \
  --input batch.yaml \
  --verbose

  5. Report Results

    • Summary: X/Y issues created/updated successfully
    • List any failures with error messages
    • Offer to save results to file

Example Interaction:

User: "Create issues from roadmap.yaml"
Skill: *Loads file, validates, executes batch*
Result: "✅ Created 25/25 issues successfully:
  - 10 features
  - 8 tasks
  - 7 bugs
  All issues added to Q1 Roadmap project"

Workflow 5: Generate Report

Trigger: User wants team/sprint metrics or status summary

Steps:

  1. Determine Report Type

    • Team Summary: Overall team metrics (by state, priority, assignee)
    • Sprint Report: Activity over time period (created, completed, velocity)

  2. Set Parameters

    • Team name
    • Time period (for sprint reports)
    • Output format (markdown or JSON)

  3. Generate Report

    • Use helpers/reporting.py
    • Example:
      python helpers/reporting.py \
  --team "Backend Team" \
  --report sprint \
  --period 7 \
  --format markdown

  4. Format Output

    • Display report in readable format
    • Highlight key metrics
    • Offer to save to file

Example Interaction:

User: "Show me the backend team's sprint summary for the last week"
Skill: *Generates sprint report*
Result: "# Sprint Report: Backend Team

Period: Last 7 days

Activity:
- Issues Created: 12
- Issues Completed: 8
- Velocity: 8 issues/week

By State:
- In Progress: 15
- Done: 42
- Backlog: 23

Would you like me to save this report?"

Helper Script Usage

Create Issue

cd /home/user/writing_ecosystem/.claude/skills/linear-agent

# Simple issue
python helpers/create_issue.py \
  --team "Backend Team" \
  --title "Add rate limiting"

# With template
python helpers/create_issue.py \
  --team "Backend" \
  --template bug_report \
  --var short_description="Login timeout" \
  --var detailed_description="Users report 30s timeout" \
  --var expected="Login within 3s" \
  --var actual="30s timeout"

Update Issue

# Change status
python helpers/update_issue.py \
  --issue-id ISS-123 \
  --state "In Progress" \
  --comment "Starting work"

# Update multiple fields
python helpers/update_issue.py \
  --issue-id ISS-124 \
  --priority 1 \
  --assignee "user_xyz" \
  --labels "urgent,bug"

Query Issues

# Filter by team and state
python helpers/query_issues.py \
  --team "Backend Team" \
  --state "In Progress"

# Search by keyword
python helpers/query_issues.py \
  --search "authentication" \
  --limit 20

# Export to CSV
python helpers/query_issues.py \
  --team "Backend" \
  --output issues.csv \
  --format csv

Bulk Operations

# Create from YAML
python helpers/bulk_operations.py \
  --action create \
  --input batch.yaml

# Update from JSON
python helpers/bulk_operations.py \
  --action update \
  --input updates.json

Reporting

# Team summary
python helpers/reporting.py \
  --team "Backend Team" \
  --report summary

# Sprint report
python helpers/reporting.py \
  --team "Backend" \
  --report sprint \
  --period 7 \
  --output sprint_report.md

Environment Setup

Required Environment Variables:

LINEAR_API_KEY=lin_api_...  # Your Linear API key

Optional:

LINEAR_WORKSPACE_ID=...     # Default workspace (if multiple)

Get API Key:

  1. Go to Linear Settings → API
  2. Create new personal API key
  3. Set as environment variable

Templates

Bug Report Template Variables

  • short_description: Brief bug summary
  • detailed_description: Detailed explanation
  • steps: Steps to reproduce
  • expected: Expected behavior
  • actual: Actual behavior
  • os: Operating system
  • version: Software version

Feature Request Template Variables

  • short_description: Brief feature summary
  • problem: Problem statement
  • solution: Proposed solution
  • alternatives: Alternative approaches
  • success_criteria: Definition of done

Task Template Variables

  • short_description: Task title
  • detailed_description: Task details
  • acceptance_criteria: Completion criteria

Best Practices

Creating Issues

  1. Use templates for bugs and features (ensures consistency)
  2. Set priority based on urgency and impact
  3. Add labels for categorization and filtering
  4. Include estimates to track effort
  5. Assign to team members with capacity

Updating Issues

  1. Add comments when making significant changes
  2. Validate state transitions (don't skip states)
  3. Update estimates as work progresses
  4. Keep descriptions current with new information

Bulk Operations

  1. Validate batch files before executing
  2. Use dry-run mode for large batches
  3. Monitor progress during execution
  4. Save results for audit trail

Reporting

  1. Generate weekly sprint reports for team visibility
  2. Track velocity trends over time
  3. Monitor workload distribution to prevent burnout
  4. Review label usage to ensure proper categorization

Troubleshooting

"Team not found"

  • Verify team name matches exactly (case-sensitive)
  • List all teams: python helpers/linear_client.py

"Label not found"

  • Check label exists for that team
  • List labels: Use Linear client to query labels

"Rate limit exceeded"

  • Client automatically throttles at 1400 requests/hour
  • Wait for rate limit window to reset
  • Consider batching operations

Authentication errors

  • Verify LINEAR_API_KEY is set correctly
  • Check API key hasn't expired
  • Ensure key has necessary permissions

Reference Documentation

See reference/ directory for:

  • linear_api_schema.md: GraphQL schema reference
  • field_mappings.md: Field mapping guide

See learnings/ directory for:

  • pitfalls.md: Common mistakes and how to avoid them