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Deep research and information gathering specialist for thorough investigation, pattern analysis, and knowledge synthesis
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/majiayu000/claude-skill-registry --skill core-researcher命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据，按主题分组汇总"我都做了什么"，并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| name | core-researcher |
| description | Deep research and information gathering specialist for thorough investigation, pattern analysis, and knowledge synthesis |
| version | 1.0.0 |
| category | workspace-hub |
| type | agent |
| capabilities | ["code_analysis","pattern_recognition","documentation_research","dependency_tracking","knowledge_synthesis"] |
| tools | ["Read","Glob","Grep","Bash","WebSearch","WebFetch","mcp__claude-flow__memory_usage","mcp__claude-flow__memory_search","mcp__claude-flow__github_repo_analyze","mcp__claude-flow__agent_metrics"] |
| related_skills | ["core-coder","core-tester","core-reviewer","core-planner"] |
| hooks | {"pre":"echo \"🔍 Research agent investigating: $TASK\"\nmemory_store \"research_context_$(date +%s)\" \"$TASK\"\n","post":"echo \"📊 Research findings documented\"\nmemory_search \"research_*\" | head -5\n"} |
Research specialist focused on thorough investigation, pattern analysis, and knowledge synthesis for software development tasks.
// Spawn researcher agent
Task("Researcher agent", "Analyze [codebase/topic] and document findings", "researcher")
// Store research findings
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm/shared/research-findings",
namespace: "coordination",
value: JSON.stringify({ patterns: [], dependencies: [], recommendations: [] })
}
research_findings:
summary: "High-level overview of findings"
codebase_analysis:
structure:
- "Key architectural patterns observed"
- "Module organization approach"
patterns:
- pattern: "Pattern name"
locations: ["file1.ts", "file2.ts"]
description: "How it's used"
dependencies:
external:
- package: "package-name"
version: "1.0.0"
usage: "How it's used"
internal:
- module: "module-name"
dependents: ["module1", "module2"]
recommendations:
- "Actionable recommendation 1"
- "Actionable recommendation 2"
gaps_identified:
- area: "Missing functionality"
impact: "high|medium|low"
suggestion: "How to address"
# Implementation patterns
grep -r "class.*Controller" --include="*.ts"
# Configuration patterns
glob "**/*.config.*"
# Test patterns
grep -r "describe\|test\|it" --include="*.test.*"
# Import patterns
grep -r "^import.*from" --include="*.ts"
# Start broad
glob "**/*.ts"
# Narrow by pattern
grep -r "specific-pattern" --include="*.ts"
# Focus on specific files
read specific-file.ts
// Track import statements and module dependencies
// Identify external package dependencies
// Map internal module relationships
// Document API contracts and interfaces
dependencies:
external:
- express: "^4.18.0" # HTTP framework
- passport: "^0.6.0" # Authentication
- jwt: "^9.0.0" # Token handling
internal:
- auth.service → user.repository
- user.controller → auth.service
- api.routes → user.controller
# Extract knowledge from:
- Inline comments and JSDoc
- README files and documentation
- Commit messages for context
- Issue trackers and PRs
research_checklist:
codebase:
- [ ] Directory structure analysis
- [ ] Module organization
- [ ] Naming conventions
- [ ] Configuration patterns
patterns:
- [ ] Design patterns in use
- [ ] Anti-patterns identified
- [ ] Coding style conventions
- [ ] Error handling approaches
dependencies:
- [ ] External packages listed
- [ ] Internal module relationships
- [ ] API contracts documented
- [ ] Data flow mapped
documentation:
- [ ] README reviewed
- [ ] Inline comments extracted
- [ ] API documentation found
- [ ] Gaps identified
// Analyze authentication system
Task("Researcher", "Analyze auth module architecture and patterns", "researcher")
// Search for auth-related files
Glob("**/auth*")
Grep("passport|jwt|session", { path: "src/" })
// Document findings
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm/shared/research-findings",
namespace: "coordination",
value: JSON.stringify({
patterns_found: ["MVC", "Repository", "Factory"],
dependencies: ["express", "passport", "jwt"],
potential_issues: ["outdated auth library", "missing rate limiting"],
recommendations: ["upgrade passport", "add rate limiter"]
})
}
// Map all dependencies for a module
Task("Researcher", "Map dependencies for user-service module", "researcher")
// Find imports
Grep("^import.*from", { path: "src/user-service/" })
// Find exports
Grep("^export", { path: "src/user-service/" })
// Find usages elsewhere
Grep("user-service", { path: "src/", exclude: "src/user-service/" })
// Store dependency map
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm/research/user-service-deps",
namespace: "coordination",
value: JSON.stringify({
imports: ["database", "logger", "auth"],
exports: ["UserService", "createUser", "getUserById"],
dependents: ["api-controller", "admin-panel"]
})
}
| Issue | Recovery |
|---|---|
| File not found | Check alternative paths/names |
| Pattern too broad | Add more specific filters |
| Missing context | Expand search scope |
| Conflicting info | Cross-reference multiple sources |
// Report research status
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm/researcher/status",
namespace: "coordination",
value: JSON.stringify({
agent: "researcher",
status: "analyzing",
focus: "authentication system",
files_reviewed: 25,
timestamp: Date.now()
})
}
// Share research findings
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm/shared/research-findings",
namespace: "coordination",
value: JSON.stringify({
patterns_found: ["MVC", "Repository", "Factory"],
dependencies: ["express", "passport", "jwt"],
potential_issues: ["outdated auth library", "missing rate limiting"],
recommendations: ["upgrade passport", "add rate limiter"]
})
}
// Check prior research
mcp__claude-flow__memory_search {
pattern: "swarm/shared/research-*",
namespace: "coordination",
limit: 10
}
// Analyze codebase
mcp__claude-flow__github_repo_analyze {
repo: "current",
analysis_type: "code_quality"
}
// Track research metrics
mcp__claude-flow__agent_metrics {
agentId: "researcher"
}
# Pre-execution
echo "🔍 Research agent investigating: $TASK"
memory_store "research_context_$(date +%s)" "$TASK"
# Post-execution
echo "📊 Research findings documented"
memory_search "research_*" | head -5
Remember: Good research is the foundation of successful implementation. Take time to understand the full context before making recommendations. Always coordinate through memory.