Synaptic SkillsSynapticSkills
MarketplaceSkill GraphCriar SkillMCP ServerPlataformaEnterprise
v0.1.0-beta
Voltar ao Marketplace
AgentsMédio

Ralph Wiggum

porfstandhartinger·fstandhartinger· v1.0.0 · atualizado em 2026-04-10
82
Score

Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.

autonomous-agentsspec-driven-developmentai-codingiterative-developmentllm-workflowagent-loopcontinuous-integration
0Stars
0Forks
0Usos
Fork

Documento do Skill

SKILL.mdralph-wiggum/workflow
1
Pick Spec: — Select a feature specification from the `specs/` directory.
2
Implement: — The AI agent writes code to implement the feature.
3
Test: — Run tests to verify the implementation against acceptance criteria.
4
Commit: — Commit the changes to the repository.
5
Check Completion: — Verify that all acceptance criteria are met and tests pass.
6
Output Completion Signal: — If all criteria are met, output `<promise>DONE</promise>`.
7
Repeat: — Move to the next specification and repeat the process.

Telemetria de Agentes

Execuções
0
total
Taxa de Sucesso
0%
últimos 30d
Latência Média
0.0s
p50
Alucinação
0.0%
detecção
Tokens Entrada
0
avg 0/exec
Tokens Saída
0
avg 0/exec

Uso por Plataforma

Skills Relacionados

Compõe comCode Review Skill
70%
Hebbian Synapse
Composite0.700
w = 0.3·α + 0.5·β + 0.2·γ
79
Similar aRemembering Conversations
60%
Hebbian Synapse
Composite0.600
w = 0.3·α + 0.5·β + 0.2·γ
80
Similar aInstaclaw 🦞
60%
Hebbian Synapse
Composite0.600
w = 0.3·α + 0.5·β + 0.2·γ
78
Similar aNotebookLM Automation
60%
Hebbian Synapse
Composite0.600
w = 0.3·α + 0.5·β + 0.2·γ
82

Árvore do Skill

Ralph Wiggum
ralph-wiggum
Fases Cognitivas6
1.SENSE
2.CONTEXTUALIZE
3.HYPOTHESIZE
4.ACT
5.EVALUATE
6.REFLECT
Triggers7
implement features autonomouslyuse ralph wiggum to build softwarerun an ai coding loopdevelop with spec driven developmentiterate on features with an ai agentautomate software development taskscode using acceptance criteria

Avaliar este Skill

Score Breakdown

⭐Avaliação Humana0%
🤖Sucesso de Agentes0%
🕐Atualidade100%
🔗Saúde de Dependências100%
🕸️Centralidade no Grafo0%
🛡️Segurança50%
CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download ralph-wiggum
$ synaptic skills detail ralph-wiggum
$ synaptic skills live ralph-wiggum

Links

GitHub Repository