Receber por email
← Voltar para o catálogo

vibecosystem

AI software team for Claude Code - 138 agents, 295 skills, 73 hooks. Self-learning, multi-agent swarm, autonomous skill evolution.

507estrelas
Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

Como adicionar

/plugin marketplace add vibeeval/vibecosystem

O comando exato pode variar conforme o repositório. Confira o README no GitHub.

Para o autor da skill

Cole no README do seu repo

Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.

[![Skillteca](https://www.skillteca.com.br/api/badge/vibecosystem-mpsjida2/svg)](https://www.skillteca.com.br/skills/vibecosystem-mpsjida2)
#ai

Skills relacionadas

Ver todas de Desenvolvimento →

Alerta por categoria

Receba novas skills de Desenvolvimento toda segunda

1 email curto, só com as skills novas de Desenvolvimento. 4 minutos de leitura, sem spam, cancela com 1 clique.

Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.

Ler descrição completa

Recall Past Work

Search through previous sessions to find relevant decisions, approaches that worked, and approaches that failed. Queries two sources:

  1. Artifact Index - Handoffs, plans, ledgers with post-mortems (what worked/failed)
  2. Reasoning Files - Build attempts, test failures, commit context

When to Use

  • Starting work similar to past sessions
  • "What did we do last time with X?"
  • Looking for patterns that worked before
  • Investigating why something was done a certain way
  • Debugging an issue encountered previously

Usage

Primary: Artifact Index (rich context)

uv run python scripts/core/artifact_query.py "<query>" [--outcome SUCCEEDED|FAILED] [--limit N]

This searches handoffs with post-mortems (what worked, what failed, key decisions).

Secondary: Reasoning Files (build attempts)

bash "$CLAUDE_PROJECT_DIR/.claude/scripts/search-reasoning.sh" "<query>"

This searches .git/claude/commits/*/reasoning.md for build failures and fixes.

Examples

# Search for authentication-related work
uv run python scripts/core/artifact_query.py "authentication OAuth JWT"

# Find only successful approaches
uv run python scripts/core/artifact_query.py "implement agent" --outcome SUCCEEDED

# Find what failed (to avoid repeating mistakes)
uv run python scripts/core/artifact_query.py "hook implementation" --outcome FAILED

# Search build/test reasoning
bash "$CLAUDE_PROJECT_DIR/.claude/scripts/search-reasoning.sh" "TypeError"

What Gets Searched

Artifact Index (handoffs, plans, ledgers):

  • Task summaries and status
  • What worked - Successful approaches
  • What failed - Dead ends and why
  • Key decisions - Choices with rationale
  • Goal and constraints from ledgers

Reasoning Files (.git/claude/):

  • Failed build attempts and error output
  • Successful builds after failures
  • Commit context and branch info

Interpreting Results

From Artifact Index:

  • ✓ = SUCCEEDED outcome (pattern to follow)
  • ✗ = FAILED outcome (pattern to avoid)
  • ? = UNKNOWN outcome (not yet marked)
  • Post-mortem sections show distilled learnings

From Reasoning:

  • build_fail = approach that didn't work
  • build_pass = what finally succeeded
  • Multiple failures before success = non-trivial problem

Process

  1. Run Artifact Index query first - richer context, post-mortems
  2. Review relevant handoffs - check what worked/failed sections
  3. If needed, search reasoning - for specific build errors
  4. Apply learnings - follow successful patterns, avoid failed ones

No Results?

Artifact Index empty:

  • Run uv run python scripts/core/artifact_index.py --all to index existing handoffs
  • Create handoffs with post-mortem sections for future recall

Reasoning files empty:

  • Use /commit after builds to capture reasoning
  • Check if .git/claude/ directory exists
Compartilhar X LinkedIn