Agent skill

Task Intelligence

by majiayu000 in majiayu000/claude-skill-registry

Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário.

MITAuto-check: notes

Install Task Intelligence

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bash/task-intelligence .claude/skills/task-intelligence && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .claude/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/bash/task-intelligence .agents/skills/task-intelligence && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .agents/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/bash/task-intelligence .cursor/skills/task-intelligence && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .cursor/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/majiayu000/claude-skill-registry.git --path skills/bash/task-intelligence

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/bash/task-intelligence .gemini/skills/task-intelligence && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .gemini/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/bash/task-intelligence .github/skills/task-intelligence && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .github/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry task-intelligence --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/bash/task-intelligence .opencode/skills/task-intelligence && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "task-intelligence" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/task-intelligence into .opencode/skills/task-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "task-intelligence", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: task-intelligence
GitHub stars: 666
Used in: 3 other repos
Token cost: ~2.9k tokens
SKILL.md length: 939 words
Files: 2
Skills in repo: 1,273
Repo updated: Oct 7, 2026
First seen: Oct 8, 2026
Licence: MIT

At a glance

Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário.

Works in 5 steps: Ativa todos os agentes relevantes em… → Sintetiza o conhecimento coletivo em um… → Estima tempo real do início ao fim (com… → …
SKILL.md covers Overview, When to Use This Skill, Do Not Use This Skill When and How It Works, plus 14 more sections
Calls python and git

What it does

Task Intelligence is an agent skill from majiayu000/claude-skill-registry. Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It works with Bash. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

Example prompts

“/task-intelligence”

Requirements

Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

Ativa todos os agentes relevantes em paralelo — cada um analisa a tarefa pela sua ótica
Sintetiza o conhecimento coletivo em um plano unificado
Estima tempo real do início ao fim (com breakdown por etapa)
Mapeia problemas prováveis e os resolve antecipadamente
Define pontos de verificação para detectar desvios antes que virem bloqueadores

What it can do on your machine

Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python
- git
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Task Intelligence loads about 2.9k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 939 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~41
When it runs · the whole SKILL.md, loaded when a task matches: ~2.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteMentions a .env fileSKILL.md:255

Usar variáveis de ambiente (.env). Webhooks precisam validação HMAC-SHA256.

NoteMentions a .env fileSKILL.md:274

✅ API key exposta → .env obrigatório, .gitignore configurado

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 939 words, ~2,900 tokens.

Download SKILL.mdSave it as .claude/skills/task-intelligence/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: task-intelligence
description: Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário.
risk: none
source: community
date_added: 2026-03-06
author: renat
tags: planning, pre-task, risk-analysis, orchestration
tools: claude-code, antigravity, cursor, gemini-cli, codex-cli

Task Intelligence — Protocolo de Amplificação Pré-Tarefa

Overview

Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário. Enriquece o contexto com análise paralela multi-agente, produz estimativa real de tempo (início→fim), mapeia problemas prováveis e improvável, e formula um plano de execução antecipado com estratégias de contingência.

When to Use This Skill

When the user mentions "pre-task briefing" or related topics
When the user mentions "briefing tarefa" or related topics
When the user mentions "plano execucao tarefa" or related topics
When the user mentions "antes de executar analise" or related topics
When the user mentions "task intelligence" or related topics
When the user mentions "consultar agentes paralelo" or related topics

Do Not Use This Skill When

The task is unrelated to task intelligence
A simpler, more specific tool can handle the request
The user needs general-purpose assistance without domain expertise

How It Works

Antes de qualquer execução, este agente realiza um briefing inteligente completo:

Ativa todos os agentes relevantes em paralelo — cada um analisa a tarefa pela sua ótica
Sintetiza o conhecimento coletivo em um plano unificado
Estima tempo real do início ao fim (com breakdown por etapa)
Mapeia problemas prováveis e os resolve antecipadamente
Define pontos de verificação para detectar desvios antes que virem bloqueadores

A razão central: executar uma tarefa sem esse briefing é como cirurgiar sem exame pré-operatório. O custo de 30-60 segundos de análise paralela elimina horas de retrabalho.

Fase 1 — Classificação Da Tarefa (5-10 Segundos)

Antes de qualquer coisa, classifique a tarefa em uma das categorias:

Categoria	Exemplos	Nível de Briefing
Simples	responder pergunta, explicar conceito, pequena edição	Mínimo (só scan)
Moderada	criar arquivo, modificar skill, instalar dependência	Normal (scan + match + estimativa)
Complexa	criar skill nova, integração API, arquitetura, refatoração	Completo (todos os passos abaixo)
Crítica	ações irreversíveis, deploys, delete, reset, modificar infra	Máximo + confirmação explícita

Para tarefas Simples, execute normalmente sem briefing completo. Para Moderada, Complexa e Crítica, execute o protocolo completo abaixo.

Fase 2 — Scan E Match Paralelo

Execute simultaneamente:

bash


## Terminal 1 — Atualizar Registry

python agent-orchestrator/scripts/scan_registry.py

## Terminal 2 — Identificar Agentes Relevantes

python agent-orchestrator/scripts/match_skills.py "<tarefa do usuário>"

Se matched >= 2, execute orquestração:

bash

python agent-orchestrator/scripts/orchestrate.py --skills <skill1,skill2,...> --query "<tarefa>"

Fase 3 — Briefing Dos Agentes Especializados

Para cada agente relevante identificado no match, faça uma pergunta direcionada:

Padrão de consulta por tipo de agente:

007 (Segurança): "Esta tarefa tem vetores de ataque, dados expostos, ou ações irreversíveis?"
skill-sentinel (Qualidade): "Existe skill redundante? A skill que será criada/modificada segue os padrões?"
agent-orchestrator (Orquestração): "Quais skills já existem que resolvem parte desta tarefa?"
matematico-tao (Complexidade): "Qual a complexidade computacional? Há otimizações não-óbvias?"
context-guardian (Continuidade): "Existe contexto de sessões anteriores relevante para esta tarefa?"
advogado-especialista/criminal (Legal): "Há implicações legais, LGPD, ou riscos regulatórios?"
leiloeiro-ia (Leilões): "Esta tarefa envolve dados ou lógica do domínio de leilões?"

Não consulte todos os agentes cegamente — escolha os 3-5 mais relevantes para a tarefa.

Fase 4 — Estimativa De Tempo Real

Construa um breakdown de tempo honesto com base na complexidade real:

ESTIMATIVA DE TEMPO — [Nome da Tarefa]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Etapa 1: [nome]          ~X min   [motivo do tempo]
Etapa 2: [nome]          ~X min   [motivo do tempo]
Etapa 3: [nome]          ~X min   [motivo do tempo]
Contingência (problemas) +X min   [buffer para imprevistos típicos]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
TOTAL ESTIMADO:          ~X min
Confiança: Alta/Média/Baixa — [justificativa]

Regras de estimativa honesta:

Nunca subestime para agradar — o usuário precisa saber o tempo real
Adicione sempre 20-30% de buffer para problemas típicos
Se a confiança for Baixa, explique por quê e o que aumentaria ela
Diferencie "tempo de execução do agente" vs "tempo de espera do usuário"

Fase 5 — Mapa De Problemas (Antecipação Proativa)

Pense em TRÊS camadas de problemas:

Show full SKILL.md (400 more words)Show less

Problemas Prováveis (80%+ de chance de acontecer)

São os problemas que SEMPRE acontecem. Resolva-os ANTES de começar.

Exemplos por categoria:

Skills novas: YAML inválido → valide com python -c "import yaml; yaml.safe_load(open('SKILL.md').read())" antes de instalar
APIs externas: chave expirada, rate limit, mudança de endpoint → verifique autenticação primeiro
Instalações: dependências faltando, versão incompatível → leia requirements.txt antes de executar
Arquivos: path não existe, permissão negada, encoding errado → verifique antes de abrir
Git/Versionamento: branch errada, conflito de merge, uncommitted changes → sempre git status antes

Problemas Possíveis (30-70% de chance)

Problemas que podem acontecer dependendo do estado atual.

Estratégia: verifique rapidamente o estado antes de assumir que está OK.

Problemas Improváveis mas Críticos (< 10% mas alto impacto)

Ações irreversíveis, perda de dados, exposição de credenciais.

Estratégia: backup preventivo, confirmação explícita, rollback plan.

Template de mapa de problemas:

MAPA DE PROBLEMAS — [Nome da Tarefa]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
PROVÁVEIS (resolver antes de começar):
  ⚠ [problema] → [solução preventiva aplicada agora]
  ⚠ [problema] → [solução preventiva aplicada agora]

POSSÍVEIS (monitorar durante execução):
  ~ [problema] → [sinal de alerta] → [ação se ocorrer]

CRÍTICOS (baixa prob, alto impacto):
  🔴 [risco] → [backup/rollback plan]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Fase 6 — Plano De Execução Enriquecido

Depois de coletar análises dos agentes + estimativas + mapa de problemas, produza:

BRIEFING PRÉ-EXECUÇÃO — [Nome da Tarefa]
════════════════════════════════════════════
CONTEXTO COLETADO:
  • [insight do agente 1]
  • [insight do agente 2]
  • [insight do agente 3]

PLANO DE EXECUÇÃO:
  1. [etapa] (~Xmin) — [por quê esta ordem]
  2. [etapa] (~Xmin) — [dependência da anterior]
  3. [etapa] (~Xmin) — [verificação de qualidade]

TEMPO TOTAL: ~Xmin | CONFIANÇA: Alta/Média/Baixa

PROBLEMAS PRÉ-RESOLVIDOS:
  ✅ [problema] → [solução aplicada]
  ✅ [problema] → [solução aplicada]

PONTOS DE VERIFICAÇÃO:
  [ ] Após etapa 1: verificar [critério de sucesso]
  [ ] Após etapa 2: verificar [critério de sucesso]
  [ ] Final: validar resultado completo

ROLLBACK PLAN (se algo der errado):
  → [como desfazer cada etapa crítica]
════════════════════════════════════════════

Integração Com O Ecossistema

Este agente complementa o agent-orchestrator — não substitui:

agent-orchestrator: identifica QUAIS skills usar (routing)
task-intelligence: enriquece COMO usar + quando + com que riscos (briefing)

Ambos devem ser ativados juntos. O CLAUDE.md já exige o orchestrator — este agente adiciona a camada de inteligência sobre ele.

Quando Não Usar O Briefing Completo

Perguntas rápidas de 1 linha (responder diretamente é mais eficiente)
Tarefas de leitura pura (read, grep, glob sem efeitos colaterais)
Iterações simples dentro de uma tarefa já planejada
Quando o usuário pede "só responde rápido" / "vibe comigo"

O objetivo não é burocracia — é inteligência a serviço da velocidade real.

Referências

references/problem-catalog.md — Catálogo de problemas típicos por domínio
references/time-patterns.md — Padrões históricos de tempo por tipo de tarefa
scripts/pre_task_check.py — Script de verificação automatizada pré-tarefa

Exemplo De Briefing Completo

Tarefa do usuário: "Crie uma skill para integração com Stripe"

BRIEFING PRÉ-EXECUÇÃO — Skill: stripe-integration
════════════════════════════════════════════════════

CONTEXTO COLETADO (3 agentes consultados):
  • 007: CRÍTICO — API keys do Stripe NÃO devem ir para SKILL.md ou git.
    Usar variáveis de ambiente (.env). Webhooks precisam validação HMAC-SHA256.
  • skill-sentinel: whatsapp-cloud-api já implementa padrão HMAC-SHA256 para webhooks
    — reusar esse padrão. Skill deve seguir estrutura: config.py + client.py + SKILL.md.
  • agent-orchestrator: 3 skills similares (whatsapp, telegram, instagram) como referência
    de arquitetura. Nenhuma conflita com Stripe.

PLANO DE EXECUÇÃO:
  1. Criar estrutura de diretórios (~2min) — base para os demais arquivos
  2. Escrever SKILL.md com workflow (~5min) — define comportamento do agente
  3. Criar config.py com variáveis de ambiente (~3min) — sem hardcode de keys
  4. Criar stripe_client.py com autenticação (~10min) — métodos principais
  5. Criar webhook_handler.py com HMAC-SHA256 (~5min) — reusar padrão whatsapp
  6. Instalar via skill-installer (~2min) — validação + registro
  7. Gerar ZIP (~1min) — para backup/upload manual

TEMPO TOTAL: ~28min | CONFIANÇA: Alta
(estrutura clara, dependências conhecidas, sem APIs externas incertas)

PROBLEMAS PRÉ-RESOLVIDOS:
  ✅ API key exposta → .env obrigatório, .gitignore configurado
  ✅ YAML inválido → validar antes de instalar
  ✅ Webhook sem autenticação → HMAC-SHA256 incluído no plano

PONTOS DE VERIFICAÇÃO:
  [ ] Após SKILL.md: yaml.safe_load não levanta exceção
  [ ] Após config.py: sem strings hardcoded de credenciais
  [ ] Final: skill-installer valida os 10 checks

ROLLBACK PLAN:
  → Se skill-installer falhar: pasta em /tmp/stripe-skill-backup/
  → Se ZIP corrompido: reconstruir com build_ecosystem.py
════════════════════════════════════════════════════

Best Practices

Provide clear, specific context about your project and requirements
Review all suggestions before applying them to production code
Combine with other complementary skills for comprehensive analysis

Common Pitfalls

Using this skill for tasks outside its domain expertise
Applying recommendations without understanding your specific context
Not providing enough project context for accurate analysis

agent-orchestrator - Complementary skill for enhanced analysis
multi-advisor - Complementary skill for enhanced analysis

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Files

SKILL.md and 1 other file in skills/bash/task-intelligence of majiayu000/claude-skill-registry.

SKILL.md
metadata.json

Open the folder on GitHubat commit 2d14a69

Used in 3 other repositories

We found 12 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 8, 2026.

Compare with similar skills

Task Intelligence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Task Intelligence compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Task Intelligence this skillmajiayu000/claude-skill-registry	666	3 repos	~2.9k	Automated safety check: Notes	MIT	today
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official	38k	11 repos	~4.1k	Automated safety check: Notes	Apache-2.0	today
Plugin Settings Patternanthropics/claude-plugins-official	38k	7 repos	~3k	Automated safety check: Pass	Apache-2.0	today
Mole Bug Patternstw93/Mole	70k	—	~2k	Automated safety check: Pass	GPL-3.0	today
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills	21k	—	~1.9k	Automated safety check: Pass	MIT	6 days ago
E2Ecallstack/react-native-pager-view	3.4k	1 repos	~2.1k	Automated safety check: Pass	MIT	today

Similar skills

Hook Development for Claude Code Plugins
anthropics/claude-plugins-official
Official
Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
38k GitHub starsUsed in 11 repos~4.1k tokens
Agent WorkflowsAuto-check: notes
Plugin Settings Pattern
anthropics/claude-plugins-official
Official
Shows how Claude Code plugins keep per-project settings and state in .claude/plugin-name.local.md files with YAML frontmatter and a markdown body.
38k GitHub starsUsed in 7 repos~3k tokens
Agent WorkflowsAuto-check passed
Mole Bug Patterns
tw93/Mole
A catalog of recurring bug shapes in the Mole Mac cleaner, used to review safety-sensitive diffs for deletion safety, unbounded commands, shell traps and weak tests.
70k GitHub stars~2k tokensUpdated today
DevelopmentAuto-check passed
Neat-Freak Knowledge Closeout
KKKKhazix/khazix-skills
Brings project docs, agent rule files, authorized memory and leftover workspace files back in line with what the code and runtime actually do at the end of a work session.
21k GitHub stars~1.9k tokensUpdated 6 days ago
Agent WorkflowsAuto-check passed
E2E
callstack/react-native-pager-view
Agentic end-to-end tests with e2e, the e2e runner. An agent skill from callstack/react-native-pager-view.
3.4k GitHub starsUsed in 1 repo~2.1k tokens
Testing & QAAuto-check passed
CCPM Project Management
automazeio/ccpm
Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.
8.4k GitHub stars~1.1k tokensUpdated 6 mo ago
Product & Project ManagementAuto-check passed

Questions about Task Intelligence

What does Task Intelligence do?

Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário. Task Intelligence is an agent skill from majiayu000/claude-skill-registry. Protocolo de Inteligência Pré-Tarefa — ativa TODOS os agentes relevantes do ecossistema ANTES de executar qualquer tarefa solicitada pelo usuário.

How do I install Task Intelligence in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a claude-code`. Or copy the skill folder (skills/bash/task-intelligence in majiayu000/claude-skill-registry) into .claude/skills/task-intelligence in your project. Claude Code loads it when a task matches its description.

How do I install Task Intelligence in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a codex`. Or copy the skill folder (skills/bash/task-intelligence in majiayu000/claude-skill-registry) into .agents/skills/task-intelligence in your project. Codex loads it when a task matches its description.

Can I use Task Intelligence in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill task-intelligence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/task-intelligence, .gemini/skills/task-intelligence, .github/skills/task-intelligence and .opencode/skills/task-intelligence in your project.

What does Task Intelligence need to run?

Going by SKILL.md and its folder, Task Intelligence needs the command-line tools its instructions call (python and git). Our summary lists: Python 3.

Does Task Intelligence access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Task Intelligence safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Task Intelligence use?

Task Intelligence is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Task Intelligence use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Task Intelligence?

Skills that share tags, products or a category with Task Intelligence: Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Plugin Settings Pattern (anthropics/claude-plugins-official, 38k stars), Mole Bug Patterns (tw93/Mole, 70k stars) and Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Task Intelligence?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Task Intelligence

Facts

At a glance

What it does

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Task Intelligence — Protocolo de Amplificação Pré-Tarefa

Overview

When to Use This Skill

Do Not Use This Skill When

How It Works

Fase 1 — Classificação Da Tarefa (5-10 Segundos)

Fase 2 — Scan E Match Paralelo

Fase 3 — Briefing Dos Agentes Especializados

Fase 4 — Estimativa De Tempo Real

Fase 5 — Mapa De Problemas (Antecipação Proativa)

Problemas Prováveis (80%+ de chance de acontecer)

Problemas Possíveis (30-70% de chance)

Problemas Improváveis mas Críticos (< 10% mas alto impacto)

Fase 6 — Plano De Execução Enriquecido

Integração Com O Ecossistema

Quando Não Usar O Briefing Completo

Referências

Exemplo De Briefing Completo

Best Practices

Common Pitfalls

Related Skills

Limitations

Files

Used in 3 other repositories

Compare with similar skills

Similar skills

More from majiayu000/claude-skill-registry

Related

Questions about Task Intelligence