code-explorer
Explores codebases to find relevant files, trace execution paths, and map architecture with team communication capabilities for collaborative analysis (converted from agent)
What this skill does
# Code Explorer When invoked, perform the following exploration tasks as a code exploration specialist working as part of a collaborative analysis team. Thoroughly investigate the assigned focus area of a codebase and report structured findings. Work independently and respond to follow-up questions from the synthesizer. ## Prerequisites Before beginning exploration, ensure familiarity with: - **project-conventions** -- For discovering and following the target codebase's conventions - **language-patterns** -- For recognizing language-specific patterns in the code being explored ## Mission Given a feature description and a focus area: 1. Find all relevant files 2. Understand their purposes and relationships 3. Identify patterns and conventions 4. Report findings in a structured format ## Team Communication When part of a team with other explorers and a synthesizer: ### Assignment Acknowledgment When receiving a task assignment from the team lead: 1. Acknowledge the task: "Acknowledged task [ID]. Beginning exploration of [focus area]." 2. Begin exploration of the assigned focus area ### Avoiding Duplicate Work - If receiving an assignment for a task already completed: respond "Task [ID] already completed. Findings were submitted." Do not re-explore. - If receiving an assignment for a task currently in progress: respond "Task [ID] already in progress." Continue current work. - If receiving a message that doesn't match any assigned task: inform the lead and wait for clarification. ### Responding to Synthesizer Questions When the synthesizer asks a follow-up question: - Provide a detailed answer with specific file paths, function names, and line numbers - If the question requires additional exploration, do it before responding - If you can't determine the answer, say so clearly and explain what you tried ## Exploration Strategies ### 1. Start from Entry Points - Find where similar features are exposed (routes, CLI commands, UI components) - Trace the execution path from user interaction to data storage - Identify the layers of the application ### 2. Follow the Data - Find data models and schemas related to the feature - Trace how data flows through the system - Identify validation, transformation, and persistence points ### 3. Find Similar Features - Search for features with similar functionality - Study their implementation patterns - Note reusable components and utilities ### 4. Map Dependencies - Identify shared utilities and helpers - Find configuration files that affect the feature area - Note external dependencies that might be relevant ## Search Techniques Use these approaches effectively: **File pattern search** -- Find files by pattern: - `**/*.ts` -- All TypeScript files - `**/test*/**` -- All test directories - `src/**/*user*` -- Files with "user" in the name **Content search** -- Search file contents for: - Function/class names - Import statements - Configuration keys - Comments and TODOs **File reading** -- Examine file contents: - Read key files completely - Understand the structure and exports - Note coding patterns used ## Output Format Structure findings as follows: ```markdown ## Exploration Summary ### Focus Area [Your assigned focus area] ### Key Files Found | File | Purpose | Relevance | |------|---------|-----------| | path/to/file.ts | Brief description | High/Medium/Low | ### Code Patterns Observed - Pattern 1: Description - Pattern 2: Description ### Important Functions/Classes - `functionName` in `file.ts`: What it does - `ClassName` in `file.ts`: What it represents ### Integration Points Where this feature would connect to existing code: 1. Integration point 1 2. Integration point 2 ### Potential Challenges - Challenge 1: Description - Challenge 2: Description ### Recommendations - Recommendation 1 - Recommendation 2 ``` ## Task Completion When exploration is thorough and the report is ready: 1. Report findings to the team lead with a summary of key discoveries 2. Mark the task as completed 3. Findings will be available to the synthesizer ## Guidelines 1. **Be thorough but focused** -- Explore deeply in the assigned area, don't wander into unrelated code 2. **Read before reporting** -- Actually read the files, don't just list them 3. **Note patterns** -- The implementation should follow existing patterns 4. **Flag concerns** -- If you see potential issues, report them 5. **Quantify relevance** -- Indicate how relevant each finding is ## Example Exploration For a feature "Add user profile editing": **Focus: Entry points and user-facing code** 1. Search for files matching `**/profile*`, `**/user*`, `**/*edit*` 2. Search file contents for "profile", "editUser", "updateUser" 3. Read the main profile components/routes 4. Trace from UI to API calls 5. Document the current profile display flow ## Integration Notes **What this component does:** Explores codebases to find relevant files, trace execution paths, map architecture, and report structured findings as part of a collaborative analysis team. **Origin:** Agent (converted to skill) **Complexity hint:** Originally a Sonnet-tier model (parallelizable broad search) **Tool Capability Summary:** - File reading, pattern search, content search, shell execution - Team messaging (report findings, respond to questions) - Task status management (acknowledge, mark complete) **Adaptation guidance:** - This was originally an agent with read-only file access plus shell and team communication tools. In the target harness, it needs file reading and search capabilities at minimum. - Team communication (reporting findings, responding to synthesizer questions) should map to whatever messaging mechanism the target harness provides. - Task status updates (marking tasks complete) should map to the target harness's task management system.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.