LI

linear-data-handling

Provides patterns for reliable Linear data synchronization, exporting, and ensuring consistency between Linear and local databases.

Install

mkdir -p .claude/skills/linear-data-handling && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4856" && unzip -o skill.zip -d .claude/skills/linear-data-handling && rm skill.zip

Installs to .claude/skills/linear-data-handling

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Data synchronization, backup, and consistency patterns for Linear.
66 charsno explicit “when” trigger
Advanced

Key capabilities

  • Define a data model for Linear issues
  • Perform full synchronization of Linear issues to local storage
  • Implement incremental synchronization via webhooks
  • Perform consistency checks between Linear and local data
  • Resolve conflicts using various strategies
  • Export Linear data to JSON or CSV

How it works

The skill outlines steps for modeling Linear entities, performing full and incremental data synchronization, and checking for consistency. It also provides strategies for resolving conflicts between local and remote data.

Inputs & outputs

You give it
Linear API key, team key, webhook events, or local/remote issue data
You get back
Synchronized local database of Linear issues, sync statistics, or resolved conflict results

When to use linear-data-handling

  • Sync Linear issues to local databases
  • Create automated backups of Linear data
  • Implement conflict resolution for issue updates
  • Export Linear data to JSON or CSV
  • Handle webhook-based data updates

About this skill

Linear Data Handling

Overview

Implement reliable data synchronization, backup, and consistency for Linear integrations. Covers full sync, incremental webhook sync, JSON/CSV export, consistency checks, and conflict resolution.

Prerequisites

  • @linear/sdk with API key configured
  • Database for local storage (any ORM — Drizzle, Prisma, Knex)
  • Understanding of eventual consistency

Instructions

Step 1: Data Model Schema

// src/models/linear-entities.ts
import { z } from "zod";

export const LinearIssueSchema = z.object({
  id: z.string().uuid(),
  identifier: z.string(), // e.g., "ENG-123"
  title: z.string(),
  description: z.string().nullable(),
  priority: z.number().int().min(0).max(4),
  estimate: z.number().nullable(),
  stateId: z.string().uuid(),
  stateName: z.string(),
  stateType: z.string(),
  teamId: z.string().uuid(),
  teamKey: z.string(),
  assigneeId: z.string().uuid().nullable(),
  projectId: z.string().uuid().nullable(),
  cycleId: z.string().uuid().nullable(),
  parentId: z.string().uuid().nullable(),
  dueDate: z.string().nullable(),
  createdAt: z.string(),
  updatedAt: z.string(),
  completedAt: z.string().nullable(),
  canceledAt: z.string().nullable(),
  syncedAt: z.string(),
});

export type LinearIssue = z.infer<typeof LinearIssueSchema>;

Step 2: Full Sync

Paginate through all issues, resolve relations, and upsert locally.

import { LinearClient } from "@linear/sdk";

interface SyncStats {
  total: number;
  created: number;
  updated: number;
  deleted: number;
  errors: number;
}

async function fullSync(client: LinearClient, teamKey: string): Promise<SyncStats> {
  const stats: SyncStats = { total: 0, created: 0, updated: 0, deleted: 0, errors: 0 };
  const remoteIds = new Set<string>();

  // Paginate all issues
  let cursor: string | undefined;
  let hasNext = true;

  while (hasNext) {
    const result = await client.client.rawRequest(`
      query FullSync($teamKey: String!, $cursor: String) {
        issues(
          first: 100,
          after: $cursor,
          filter: { team: { key: { eq: $teamKey } } },
          orderBy: updatedAt
        ) {
          nodes {
            id identifier title description priority estimate
            dueDate createdAt updatedAt completedAt canceledAt
            state { id name type }
            team { id key }
            assignee { id }
            project { id }
            cycle { id }
            parent { id }
          }
          pageInfo { hasNextPage endCursor }
        }
      }
    `, { teamKey, cursor });

    const issues = result.data.issues;

    for (const issue of issues.nodes) {
      remoteIds.add(issue.id);
      stats.total++;

      try {
        const mapped: LinearIssue = {
          id: issue.id,
          identifier: issue.identifier,
          title: issue.title,
          description: issue.description,
          priority: issue.priority,
          estimate: issue.estimate,
          stateId: issue.state.id,
          stateName: issue.state.name,
          stateType: issue.state.type,
          teamId: issue.team.id,
          teamKey: issue.team.key,
          assigneeId: issue.assignee?.id ?? null,
          projectId: issue.project?.id ?? null,
          cycleId: issue.cycle?.id ?? null,
          parentId: issue.parent?.id ?? null,
          dueDate: issue.dueDate,
          createdAt: issue.createdAt,
          updatedAt: issue.updatedAt,
          completedAt: issue.completedAt,
          canceledAt: issue.canceledAt,
          syncedAt: new Date().toISOString(),
        };

        const existing = await db.issues.findById(issue.id);
        if (existing) {
          await db.issues.update(issue.id, mapped);
          stats.updated++;
        } else {
          await db.issues.insert(mapped);
          stats.created++;
        }
      } catch (error) {
        stats.errors++;
        console.error(`Error syncing ${issue.identifier}:`, error);
      }
    }

    hasNext = issues.pageInfo.hasNextPage;
    cursor = issues.pageInfo.endCursor;

    // Rate limit protection
    if (hasNext) await new Promise(r => setTimeout(r, 100));
  }

  // Soft-delete issues that no longer exist remotely
  const localIds = await db.issues.listIds({ teamKey });
  for (const localId of localIds) {
    if (!remoteIds.has(localId)) {
      await db.issues.softDelete(localId);
      stats.deleted++;
    }
  }

  console.log(`Full sync complete:`, stats);
  return stats;
}

Step 3: Incremental Sync via Webhooks

async function processWebhookSync(event: {
  action: "create" | "update" | "remove";
  type: string;
  data: any;
}) {
  if (event.type !== "Issue") return;

  const syncedAt = new Date().toISOString();

  switch (event.action) {
    case "create":
      await db.issues.insert({
        id: event.data.id,
        identifier: event.data.identifier,
        title: event.data.title,
        description: event.data.description,
        priority: event.data.priority,
        estimate: event.data.estimate,
        stateId: event.data.stateId ?? event.data.state?.id,
        stateName: event.data.state?.name ?? "Unknown",
        stateType: event.data.state?.type ?? "unknown",
        teamId: event.data.teamId ?? event.data.team?.id,
        teamKey: event.data.team?.key ?? "",
        assigneeId: event.data.assigneeId ?? null,
        projectId: event.data.projectId ?? null,
        cycleId: event.data.cycleId ?? null,
        parentId: event.data.parentId ?? null,
        dueDate: event.data.dueDate ?? null,
        createdAt: event.data.createdAt,
        updatedAt: event.data.updatedAt,
        completedAt: event.data.completedAt ?? null,
        canceledAt: event.data.canceledAt ?? null,
        syncedAt,
      });
      break;

    case "update":
      await db.issues.update(event.data.id, {
        ...event.data,
        syncedAt,
      });
      break;

    case "remove":
      await db.issues.softDelete(event.data.id);
      break;
  }
}

Step 4: Data Export / Backup

async function exportToJson(client: LinearClient, outputDir: string) {
  const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
  const teams = await client.teams();

  const backup = {
    exportedAt: new Date().toISOString(),
    version: "1.0",
    teams: teams.nodes.map(t => ({ id: t.id, key: t.key, name: t.name })),
    projects: [] as any[],
    issues: [] as any[],
  };

  // Export projects
  const projects = await client.projects();
  backup.projects = projects.nodes.map(p => ({
    id: p.id, name: p.name, state: p.state,
    targetDate: p.targetDate, progress: p.progress,
  }));

  // Export issues with pagination
  for (const team of teams.nodes) {
    let cursor: string | undefined;
    let hasNext = true;
    while (hasNext) {
      const result = await client.issues({
        first: 100,
        after: cursor,
        filter: { team: { id: { eq: team.id } } },
      });
      for (const issue of result.nodes) {
        backup.issues.push({
          id: issue.id,
          identifier: issue.identifier,
          title: issue.title,
          description: issue.description,
          priority: issue.priority,
          estimate: issue.estimate,
          createdAt: issue.createdAt,
          updatedAt: issue.updatedAt,
        });
      }
      hasNext = result.pageInfo.hasNextPage;
      cursor = result.pageInfo.endCursor;
      if (hasNext) await new Promise(r => setTimeout(r, 100));
    }
  }

  const path = `${outputDir}/linear-backup-${timestamp}.json`;
  await fs.writeFile(path, JSON.stringify(backup, null, 2));
  console.log(`Exported ${backup.issues.length} issues to ${path}`);
}

Step 5: Consistency Check

async function checkConsistency(client: LinearClient, teamKey: string): Promise<{
  missing: string[];
  stale: string[];
  orphaned: string[];
}> {
  // Sample 50 remote issues
  const remote = await client.issues({
    first: 50,
    filter: { team: { key: { eq: teamKey } } },
    orderBy: "updatedAt",
  });

  const missing: string[] = [];
  const stale: string[] = [];

  for (const issue of remote.nodes) {
    const local = await db.issues.findById(issue.id);
    if (!local) {
      missing.push(issue.identifier);
    } else if (local.updatedAt < issue.updatedAt) {
      stale.push(issue.identifier);
    }
  }

  // Find orphaned local records
  const orphaned: string[] = [];
  const localSample = await db.issues.findRecent(50);
  for (const local of localSample) {
    try {
      await client.issue(local.id);
    } catch {
      orphaned.push(local.identifier);
    }
  }

  const result = { missing, stale, orphaned };
  console.log(`Consistency check: ${missing.length} missing, ${stale.length} stale, ${orphaned.length} orphaned`);

  // Auto-trigger full sync if too many issues
  if (missing.length > 10 || stale.length > 10) {
    console.warn("High inconsistency — triggering full sync");
    await fullSync(client, teamKey);
  }

  return result;
}

Step 6: Conflict Resolution

type ConflictStrategy = "remote-wins" | "local-wins" | "merge" | "manual";

interface ConflictResult {
  resolved: boolean;
  strategy: ConflictStrategy;
  winner: "local" | "remote" | "merged";
}

function resolveConflict(
  local: LinearIssue,
  remote: any,
  strategy: ConflictStrategy,
  mergeFields?: string[]
): ConflictResult {
  switch (strategy) {
    case "remote-wins":
      // Remote always wins — standard for most integrations
      db.issues.update(remote.id, { ...remote, syncedAt: new Date().toISOString() });
      return { resolved: true, strategy, winner: "remote" };

    case "local-wins":
      // Keep local, skip remote update
      return { resolved: true, strategy, winner: "local" };

    case "merge":
      // Field-level merge — use remote for specified fields, local for rest
      const merged = { ...local };
      for (const field of mergeFields ?? ["title", "priority", 

---

*Content truncated.*

When not to use it

  • When Linear data synchronization is not needed
  • When a local database is not used for Linear data

Prerequisites

`@linear/sdk` with API key configuredDatabase for local storage

Limitations

  • Sync operations may timeout with too many records
  • Concurrent edits can lead to data conflicts
  • Missed webhook events can result in stale data

How it compares

This skill provides structured patterns for building reliable data synchronization and backup solutions for Linear, automating processes that would otherwise require manual data management.

Compared to similar skills

linear-data-handling side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
linear-data-handling (this skill)126dReviewAdvanced
bullmq-specialist256moNo flagsIntermediate
prisma-expert126moReviewIntermediate
convex-functions46moNo flagsIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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