322 skills ・ Works with: Jira · sorted by popularity
Organize Linear or Jira backlogs through the Composio CLI, a command-line tool. Fetch issues in bulk, group likely duplicates, update labels, priorities, and owners, then share a summary of changes in Slack.
Connect AI agents to Jira and Confluence through MCP, a protocol for accessing external tools. This skill guides issue searches and updates, page management, sprint workflows, authentication setup, and troubleshooting of Atlassian integrations.
Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.
Turn validated Codex Security findings into tracked work in Linear, Jira, GitHub issues, or draft GitHub security advisories. Check for duplicates, preview exact content and audience, and record approved creations, updates, or reuse.
Adapt a Claude Code or Cowork plugin to an organization's tools and workflows. Update instructions, team settings, and service connections, then package the customized files for installation while preserving the plugin's original name.
Create a Claude Cowork plugin through guided conversation, from defining its purpose to designing components and checking files. Receive a packaged .plugin file containing the skills and integrations needed for the agreed workflow.
Update individual settings in an existing product counsel profile, such as risk thresholds, escalation contacts, launch review categories, or marketing claims rules. The guided process explains downstream effects, checks inconsistencies, and saves confirmed changes without repeating setup.
Set up product legal workflows through an interview about company context, review practices, and approval routes. Past launch reviews help establish which risks block release, while connector checks record which tracking and document services actually respond.
Review a product launch against the team's legal framework and risk standards. Produce a category-by-category memo with required actions, owners, and deadlines, plus a separate tracker comment that omits internal legal reasoning.
Set up Git workflows for Gitee, Coding.net, 极狐 GitLab, and CNB with platform-specific connection and authentication examples. Choose branching rules, standardize Chinese commit messages, and adapt automated testing and deployment configurations to your team's workflow.
Turn reusable workflows and project conventions into concise instructions for AI agents. Structure SKILL.md with required metadata, move supporting material into local files, and register project skills in AGENTS.md when applicable.
Turn validated Codex Security findings into tracked issues in Linear, Jira, or GitHub, or draft GitHub security advisories. Checks duplicates and visibility, previews exact changes for approval, and verifies results after writing.
Choose charts and diagrams that fit the data and the question readers need to answer. Plan layouts and interactions for large screens and mobile devices, or critique existing visuals for misleading comparisons, unclear labels, and hidden information.
Evaluate supplied security findings against repository code and security policy without running the software. Classify each claim as confirmed, not actionable, or needing review, then rank relevant findings by exploitability and explain evidence gaps and next steps.
Design, review, and implement Gantt charts for project schedules. Assess source data, task dependencies, and resource needs, then define suitable views, editing behavior, rendering tools, accessibility, exports, and tests—or recommend a clearer alternative.
Manage Jira issues through Atlassian MCP, a connection that lets an AI agent use Jira tools. Find tasks, create issues and subtasks, update assignees, add comments, and change status using the detected project configuration.
Find and manage documentation in Confluence through Atlassian MCP, a connection to Atlassian tools. Search in plain language, read and summarize pages, create or update structured content, browse spaces, and add page comments.
Create a technical design document before implementation by answering questions about the problem, scope, architecture, risks, and delivery plan. The skill adjusts sections to project size and covers security, testing, monitoring, and recovery where relevant.
Create new Feishu cloud documents from Markdown, a text format for structured content. Choose a folder or knowledge library location, and include tables, images, and diagrams in meeting notes or project plans.
Guides you through connecting external services to Claude Code plugins using MCP, a protocol for exposing services as tools. Covers connection types, configuration files, authentication, tool permissions, and testing.
Jiraチケットの要件とConfluenceの関連ドキュメントを基に、Frontend/Backend/Infrastructureに分割した実装計画を策定するプランニングスキル。Jiraチケット情報とConfluence検索結果が前段で取得済みであることを前提とし、構造化された実装計画を出力する。「プランニング」「実装計画策定」「タスク分割」などの文脈で使用。
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Hunt LLM/AI feature bugs — prompt injection, indirect injection, exfiltration via tool-use/markdown, ASCII smuggling, agentic AI security (OWASP Agentic Apps 2026, ASI01-ASI10). Patterns: direct injection ('ignore previous instructions'), indirect injection via documents/web pages/email the model reads, ASCII smuggling (Unicode Tags block U+E0000-U+E007F, invisible to humans, decoded by the model), tool-use exfiltration (model has fetch/browse tool, attacker injects OOB URL, model exfils chat history/secrets), markdown-image zero-click exfil, system-prompt extraction, IDOR-via-AI (cross-tenant data). Targets: chatbots, RAG, summarizers, agentic copilots, MCP tools. Detection: any LLM-backed endpoint, doc upload triggering AI processing, autonomous agent with tools. Validate: OOB/Collaborator callback for exfil, verbatim-reproducible system-prompt leak (run twice), verifiable cross-tenant leak or RCE. Confabulation is NOT a finding. Use when hunting AI features, chatbots, RAG, agentic systems, MCP.
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This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
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Run Tika's OSS-Fuzz Jazzer targets locally against a working-tree checkout — build the image, build fuzzers from local source, fuzz a target, run a corpus as a regression pass, reproduce a crash, and add seeds. Use for "fuzz the OneNote parser", "run OneNoteParserFuzzer against these files", "reproduce an OSS-Fuzz crash", "fuzz my branch before merge".
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