Gere um relatório narrativo detalhado do histórico de desenvolvimento de um projeto a partir da linha do tempo do claude-mem.
Esta skill permite que agentes de IA como Claude Code, Cursor e Codex gerem relatórios narrativos completos sobre o histórico de desenvolvimento de um projeto, intitulados "Jornada em [Projeto]". Ela analisa toda a linha do tempo registrada pelo claude-mem, extraindo informações de commits, mudanças de arquivos, decisões de design e marcos importantes para construir uma história coesa. É útil para desenvolvedores que desejam entender rapidamente a evolução de um projeto, identificar padrões de desenvolvimento ou gerar documentação retrospectiva. A skill opera através da consulta ao repositório local de memória do claude-mem, processando os dados em tempo real e estruturando o relatório em seções como 'Origens', 'Principais Marcos' e 'Reflexões Técnicas'.
npx skills add https://github.com/thedotmack/claude-mem/tree/main/skills/timeline-reportInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Gere um relatório narrativo "Jornada em [Projeto]" analisando todo o histórico de desenvolvimento de um projeto a partir da linha do tempo do claude-mem. Use quando solicitado um relatório de linha do tempo, análise de histórico do projeto, jornada de desenvolvimento ou relatório completo do projeto.
This repo contains 11 individual skills — each has its own dedicated page.
Watch a pull request or review cycle until it is ready to merge. Use when asked to babysit, monitor, or keep checking PR comments, reviews, and CI until all actionable issues are resolved.
Automated semantic versioning and release workflow for Claude Code plugins. Handles version increments across package.json, marketplace.json, plugin.json manifests, build verification, git tagging, GitHub releases, and changelog generation. NPM publishing (so `npx [email protected]` resolves) is handed off to the human maintainer, who raised npm security.
Execute a phased implementation plan using subagents. Use when asked to execute, run, or carry out a plan — especially one created by make-plan.
Explain how claude-mem captures observations, when memory injection kicks in, and where data lives. Use when the user asks "how does claude-mem work?" or "what is this thing doing?".
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
Prime a codebase by reading every source file in full. Use when starting work on a new or unfamiliar project, or when the user asks to "learn the codebase", "read the codebase", "prime", or "get up to speed".
Create a detailed, phased implementation plan with documentation discovery. Use when asked to plan a feature, task, or multi-step implementation — especially before executing with do.
Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.
Map a codebase into feature-grouped flowcharts, identify duplicated concerns across features, and propose a unified architecture. Use when asked to "find the ideal path," unify duplicated systems, or audit architecture before a refactor. Emits a proposed unified flowchart plus per-system /make-plan prompts.
Token-optimized structural code search using tree-sitter AST parsing. Use instead of reading full files when you need to understand code structure, find functions, or explore a codebase efficiently.
Turn one document into a kawaii NotebookLM slide-deck PDF. Use for "wowerpoint this", "make a deck about <file>", "turn this report into slides", or any request to render a single document as shareable narrative slides.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.