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feat/v1.10
...
fix/ci-tes
| Author | SHA1 | Date | |
|---|---|---|---|
|
d728312b58 |
@@ -13,8 +13,8 @@
|
||||
{
|
||||
"name": "everything-claude-code",
|
||||
"source": "./",
|
||||
"description": "The most comprehensive Claude Code plugin — 30 agents, 140 skills, 60 commands, and production-ready hooks. Default install gets core skills; re-run with --profile full for everything. Supports Claude, Cursor, Codex, OpenCode, Gemini CLI, and Antigravity.",
|
||||
"version": "1.10.0",
|
||||
"description": "The most comprehensive Claude Code plugin — 14+ agents, 56+ skills, 33+ commands, and production-ready hooks for TDD, security scanning, code review, and continuous learning",
|
||||
"version": "1.9.0",
|
||||
"author": {
|
||||
"name": "Affaan Mustafa",
|
||||
"email": "me@affaanmustafa.com"
|
||||
|
||||
@@ -1,62 +0,0 @@
|
||||
# ECC for Gemini CLI
|
||||
|
||||
This file provides guidance to Gemini CLI when working with code in projects that have ECC installed.
|
||||
|
||||
## Overview
|
||||
|
||||
Everything Claude Code (ECC) is a production-ready AI coding plugin providing 28 agents, 127 skills, and 60 commands for software development workflows.
|
||||
|
||||
## Core Workflows
|
||||
|
||||
### Test-Driven Development
|
||||
1. Write tests first (RED)
|
||||
2. Run tests — they should fail
|
||||
3. Write minimal implementation (GREEN)
|
||||
4. Run tests — they should pass
|
||||
5. Refactor (IMPROVE)
|
||||
6. Verify 80%+ coverage
|
||||
|
||||
### Code Review
|
||||
- Check for security vulnerabilities (OWASP Top 10)
|
||||
- Verify error handling at system boundaries
|
||||
- Ensure immutable data patterns
|
||||
- Validate input at API boundaries
|
||||
|
||||
### Architecture
|
||||
- Many small files over few large files (200-400 lines, 800 max)
|
||||
- Organize by feature/domain, not by type
|
||||
- Repository pattern for data access
|
||||
- API response format: `{ success, data?, error?, meta? }`
|
||||
|
||||
## Coding Standards
|
||||
|
||||
- Prefer immutability — create new objects, never mutate
|
||||
- Functions under 50 lines
|
||||
- No deep nesting (4 levels max)
|
||||
- Validate user input with schema validation (Zod, Joi, etc.)
|
||||
- No hardcoded secrets — use environment variables
|
||||
- Handle errors comprehensively with user-friendly messages
|
||||
|
||||
## Security Checklist
|
||||
|
||||
Before any commit:
|
||||
- No hardcoded secrets
|
||||
- All user inputs validated
|
||||
- SQL injection prevention (parameterized queries)
|
||||
- XSS prevention
|
||||
- CSRF protection
|
||||
- Authentication/authorization verified
|
||||
|
||||
## Commit Format
|
||||
|
||||
```
|
||||
<type>: <description>
|
||||
```
|
||||
|
||||
Types: feat, fix, refactor, docs, test, chore, perf, ci
|
||||
|
||||
## Available Skills
|
||||
|
||||
Skills are located in the `skills/` directory. Each contains a `SKILL.md` with detailed instructions.
|
||||
|
||||
Key skills: tdd-workflow, security-review, coding-standards, backend-patterns, frontend-patterns, lead-intelligence, autonomous-agent-harness, deep-research, exa-search, x-api
|
||||
@@ -1,6 +1,6 @@
|
||||
# Everything Claude Code (ECC) — Agent Instructions
|
||||
|
||||
This is a **production-ready AI coding plugin** providing 30 specialized agents, 138 skills, 60 commands, and automated hook workflows for software development.
|
||||
This is a **production-ready AI coding plugin** providing 30 specialized agents, 136 skills, 60 commands, and automated hook workflows for software development.
|
||||
|
||||
**Version:** 1.9.0
|
||||
|
||||
@@ -142,7 +142,7 @@ Troubleshoot failures: check test isolation → verify mocks → fix implementat
|
||||
|
||||
```
|
||||
agents/ — 30 specialized subagents
|
||||
skills/ — 138 workflow skills and domain knowledge
|
||||
skills/ — 136 workflow skills and domain knowledge
|
||||
commands/ — 60 slash commands
|
||||
hooks/ — Trigger-based automations
|
||||
rules/ — Always-follow guidelines (common + per-language)
|
||||
|
||||
@@ -220,7 +220,7 @@ For manual install instructions see the README in the `rules/` folder. When copy
|
||||
/plugin list everything-claude-code@everything-claude-code
|
||||
```
|
||||
|
||||
**That's it!** You now have access to 30 agents, 138 skills, and 60 commands.
|
||||
**That's it!** You now have access to 30 agents, 136 skills, and 60 commands.
|
||||
|
||||
### Multi-model commands require additional setup
|
||||
|
||||
@@ -1111,7 +1111,7 @@ The configuration is automatically detected from `.opencode/opencode.json`.
|
||||
|---------|-------------|----------|--------|
|
||||
| Agents | PASS: 30 agents | PASS: 12 agents | **Claude Code leads** |
|
||||
| Commands | PASS: 60 commands | PASS: 31 commands | **Claude Code leads** |
|
||||
| Skills | PASS: 138 skills | PASS: 37 skills | **Claude Code leads** |
|
||||
| Skills | PASS: 136 skills | PASS: 37 skills | **Claude Code leads** |
|
||||
| Hooks | PASS: 8 event types | PASS: 11 events | **OpenCode has more!** |
|
||||
| Rules | PASS: 29 rules | PASS: 13 instructions | **Claude Code leads** |
|
||||
| MCP Servers | PASS: 14 servers | PASS: Full | **Full parity** |
|
||||
|
||||
@@ -84,7 +84,6 @@
|
||||
".claude-plugin",
|
||||
".codex",
|
||||
".cursor",
|
||||
".gemini",
|
||||
".opencode",
|
||||
"mcp-configs",
|
||||
"scripts/setup-package-manager.js"
|
||||
@@ -94,7 +93,6 @@
|
||||
"cursor",
|
||||
"antigravity",
|
||||
"codex",
|
||||
"gemini",
|
||||
"opencode"
|
||||
],
|
||||
"dependencies": [],
|
||||
@@ -275,7 +273,6 @@
|
||||
"skills/content-engine",
|
||||
"skills/investor-materials",
|
||||
"skills/investor-outreach",
|
||||
"skills/lead-intelligence",
|
||||
"skills/market-research"
|
||||
],
|
||||
"targets": [
|
||||
@@ -397,7 +394,6 @@
|
||||
"paths": [
|
||||
"skills/agent-harness-construction",
|
||||
"skills/agentic-engineering",
|
||||
"skills/autonomous-agent-harness",
|
||||
"skills/ai-first-engineering",
|
||||
"skills/autonomous-loops",
|
||||
"skills/blueprint",
|
||||
|
||||
@@ -8,6 +8,14 @@ SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||
REPO_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
|
||||
CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
|
||||
|
||||
# Use rg if available, otherwise fall back to grep -E.
|
||||
# All patterns in this script must be POSIX ERE compatible.
|
||||
if command -v rg >/dev/null 2>&1; then
|
||||
search_file() { rg -n "$1" "$2" >/dev/null 2>&1; }
|
||||
else
|
||||
search_file() { grep -En "$1" "$2" >/dev/null 2>&1; }
|
||||
fi
|
||||
|
||||
CONFIG_FILE="$CODEX_HOME/config.toml"
|
||||
AGENTS_FILE="$CODEX_HOME/AGENTS.md"
|
||||
PROMPTS_DIR="$CODEX_HOME/prompts"
|
||||
@@ -48,7 +56,7 @@ require_file() {
|
||||
check_config_pattern() {
|
||||
local pattern="$1"
|
||||
local label="$2"
|
||||
if rg -n "$pattern" "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file "$pattern" "$CONFIG_FILE"; then
|
||||
ok "$label"
|
||||
else
|
||||
fail "$label"
|
||||
@@ -58,7 +66,7 @@ check_config_pattern() {
|
||||
check_config_absent() {
|
||||
local pattern="$1"
|
||||
local label="$2"
|
||||
if rg -n "$pattern" "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file "$pattern" "$CONFIG_FILE"; then
|
||||
fail "$label"
|
||||
else
|
||||
ok "$label"
|
||||
@@ -73,13 +81,13 @@ require_file "$CONFIG_FILE" "Global config.toml"
|
||||
require_file "$AGENTS_FILE" "Global AGENTS.md"
|
||||
|
||||
if [[ -f "$AGENTS_FILE" ]]; then
|
||||
if rg -n '^# Everything Claude Code \(ECC\) — Agent Instructions' "$AGENTS_FILE" >/dev/null 2>&1; then
|
||||
if search_file '^# Everything Claude Code \(ECC\)' "$AGENTS_FILE"; then
|
||||
ok "AGENTS contains ECC root instructions"
|
||||
else
|
||||
fail "AGENTS missing ECC root instructions"
|
||||
fi
|
||||
|
||||
if rg -n '^# Codex Supplement \(From ECC \.codex/AGENTS\.md\)' "$AGENTS_FILE" >/dev/null 2>&1; then
|
||||
if search_file '^# Codex Supplement \(From ECC \.codex/AGENTS\.md\)' "$AGENTS_FILE"; then
|
||||
ok "AGENTS contains ECC Codex supplement"
|
||||
else
|
||||
fail "AGENTS missing ECC Codex supplement"
|
||||
@@ -87,11 +95,11 @@ if [[ -f "$AGENTS_FILE" ]]; then
|
||||
fi
|
||||
|
||||
if [[ -f "$CONFIG_FILE" ]]; then
|
||||
check_config_pattern '^multi_agent\s*=\s*true' "multi_agent is enabled"
|
||||
check_config_absent '^\s*collab\s*=' "deprecated collab flag is absent"
|
||||
check_config_pattern '^multi_agent[[:space:]]*=[[:space:]]*true' "multi_agent is enabled"
|
||||
check_config_absent '^[[:space:]]*collab[[:space:]]*=' "deprecated collab flag is absent"
|
||||
# persistent_instructions is recommended but optional; warn instead of fail
|
||||
# so users who rely on AGENTS.md alone are not blocked (#967).
|
||||
if rg -n '^[[:space:]]*persistent_instructions\s*=' "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file '^[[:space:]]*persistent_instructions[[:space:]]*=' "$CONFIG_FILE"; then
|
||||
ok "persistent_instructions is configured"
|
||||
else
|
||||
warn "persistent_instructions is not set (recommended but optional)"
|
||||
@@ -105,7 +113,7 @@ if [[ -f "$CONFIG_FILE" ]]; then
|
||||
'mcp_servers.sequential-thinking' \
|
||||
'mcp_servers.context7'
|
||||
do
|
||||
if rg -n "^\[$section\]" "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file "^\[$section\]" "$CONFIG_FILE"; then
|
||||
ok "MCP section [$section] exists"
|
||||
else
|
||||
fail "MCP section [$section] missing"
|
||||
@@ -115,11 +123,11 @@ if [[ -f "$CONFIG_FILE" ]]; then
|
||||
has_context7_legacy=0
|
||||
has_context7_current=0
|
||||
|
||||
if rg -n '^\[mcp_servers\.context7\]' "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file '^\[mcp_servers\.context7\]' "$CONFIG_FILE"; then
|
||||
has_context7_legacy=1
|
||||
fi
|
||||
|
||||
if rg -n '^\[mcp_servers\.context7-mcp\]' "$CONFIG_FILE" >/dev/null 2>&1; then
|
||||
if search_file '^\[mcp_servers\.context7-mcp\]' "$CONFIG_FILE"; then
|
||||
has_context7_current=1
|
||||
fi
|
||||
|
||||
|
||||
@@ -1,267 +0,0 @@
|
||||
---
|
||||
name: autonomous-agent-harness
|
||||
description: Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants continuous autonomous operation, scheduled tasks, or a self-directing agent loop.
|
||||
origin: ECC
|
||||
---
|
||||
|
||||
# Autonomous Agent Harness
|
||||
|
||||
Turn Claude Code into a persistent, self-directing agent system using only native features and MCP servers.
|
||||
|
||||
## When to Activate
|
||||
|
||||
- User wants an agent that runs continuously or on a schedule
|
||||
- Setting up automated workflows that trigger periodically
|
||||
- Building a personal AI assistant that remembers context across sessions
|
||||
- User says "run this every day", "check on this regularly", "keep monitoring"
|
||||
- Wants to replicate functionality from Hermes, AutoGPT, or similar autonomous agent frameworks
|
||||
- Needs computer use combined with scheduled execution
|
||||
|
||||
## Architecture
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────────────┐
|
||||
│ Claude Code Runtime │
|
||||
│ │
|
||||
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌─────────────┐ │
|
||||
│ │ Crons │ │ Dispatch │ │ Memory │ │ Computer │ │
|
||||
│ │ Schedule │ │ Remote │ │ Store │ │ Use │ │
|
||||
│ │ Tasks │ │ Agents │ │ │ │ │ │
|
||||
│ └────┬─────┘ └────┬─────┘ └────┬─────┘ └──────┬──────┘ │
|
||||
│ │ │ │ │ │
|
||||
│ ▼ ▼ ▼ ▼ │
|
||||
│ ┌──────────────────────────────────────────────────────┐ │
|
||||
│ │ ECC Skill + Agent Layer │ │
|
||||
│ │ │ │
|
||||
│ │ skills/ agents/ commands/ hooks/ │ │
|
||||
│ └──────────────────────────────────────────────────────┘ │
|
||||
│ │ │ │ │ │
|
||||
│ ▼ ▼ ▼ ▼ │
|
||||
│ ┌──────────────────────────────────────────────────────┐ │
|
||||
│ │ MCP Server Layer │ │
|
||||
│ │ │ │
|
||||
│ │ memory github exa supabase browser-use │ │
|
||||
│ └──────────────────────────────────────────────────────┘ │
|
||||
└──────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## Core Components
|
||||
|
||||
### 1. Persistent Memory
|
||||
|
||||
Use Claude Code's built-in memory system enhanced with MCP memory server for structured data.
|
||||
|
||||
**Built-in memory** (`~/.claude/projects/*/memory/`):
|
||||
- User preferences, feedback, project context
|
||||
- Stored as markdown files with frontmatter
|
||||
- Automatically loaded at session start
|
||||
|
||||
**MCP memory server** (structured knowledge graph):
|
||||
- Entities, relations, observations
|
||||
- Queryable graph structure
|
||||
- Cross-session persistence
|
||||
|
||||
**Memory patterns:**
|
||||
|
||||
```
|
||||
# Short-term: current session context
|
||||
Use TodoWrite for in-session task tracking
|
||||
|
||||
# Medium-term: project memory files
|
||||
Write to ~/.claude/projects/*/memory/ for cross-session recall
|
||||
|
||||
# Long-term: MCP knowledge graph
|
||||
Use mcp__memory__create_entities for permanent structured data
|
||||
Use mcp__memory__create_relations for relationship mapping
|
||||
Use mcp__memory__add_observations for new facts about known entities
|
||||
```
|
||||
|
||||
### 2. Scheduled Operations (Crons)
|
||||
|
||||
Use Claude Code's scheduled tasks to create recurring agent operations.
|
||||
|
||||
**Setting up a cron:**
|
||||
|
||||
```
|
||||
# Via MCP tool
|
||||
mcp__scheduled-tasks__create_scheduled_task({
|
||||
name: "daily-pr-review",
|
||||
schedule: "0 9 * * 1-5", # 9 AM weekdays
|
||||
prompt: "Review all open PRs in affaan-m/everything-claude-code. For each: check CI status, review changes, flag issues. Post summary to memory.",
|
||||
project_dir: "/path/to/repo"
|
||||
})
|
||||
|
||||
# Via claude -p (programmatic mode)
|
||||
echo "Review open PRs and summarize" | claude -p --project /path/to/repo
|
||||
```
|
||||
|
||||
**Useful cron patterns:**
|
||||
|
||||
| Pattern | Schedule | Use Case |
|
||||
|---------|----------|----------|
|
||||
| Daily standup | `0 9 * * 1-5` | Review PRs, issues, deploy status |
|
||||
| Weekly review | `0 10 * * 1` | Code quality metrics, test coverage |
|
||||
| Hourly monitor | `0 * * * *` | Production health, error rate checks |
|
||||
| Nightly build | `0 2 * * *` | Run full test suite, security scan |
|
||||
| Pre-meeting | `*/30 * * * *` | Prepare context for upcoming meetings |
|
||||
|
||||
### 3. Dispatch / Remote Agents
|
||||
|
||||
Trigger Claude Code agents remotely for event-driven workflows.
|
||||
|
||||
**Dispatch patterns:**
|
||||
|
||||
```bash
|
||||
# Trigger from CI/CD
|
||||
curl -X POST "https://api.anthropic.com/dispatch" \
|
||||
-H "Authorization: Bearer $ANTHROPIC_API_KEY" \
|
||||
-d '{"prompt": "Build failed on main. Diagnose and fix.", "project": "/repo"}'
|
||||
|
||||
# Trigger from webhook
|
||||
# GitHub webhook → dispatch → Claude agent → fix → PR
|
||||
|
||||
# Trigger from another agent
|
||||
claude -p "Analyze the output of the security scan and create issues for findings"
|
||||
```
|
||||
|
||||
### 4. Computer Use
|
||||
|
||||
Leverage Claude's computer-use MCP for physical world interaction.
|
||||
|
||||
**Capabilities:**
|
||||
- Browser automation (navigate, click, fill forms, screenshot)
|
||||
- Desktop control (open apps, type, mouse control)
|
||||
- File system operations beyond CLI
|
||||
|
||||
**Use cases within the harness:**
|
||||
- Automated testing of web UIs
|
||||
- Form filling and data entry
|
||||
- Screenshot-based monitoring
|
||||
- Multi-app workflows
|
||||
|
||||
### 5. Task Queue
|
||||
|
||||
Manage a persistent queue of tasks that survive session boundaries.
|
||||
|
||||
**Implementation:**
|
||||
|
||||
```
|
||||
# Task persistence via memory
|
||||
Write task queue to ~/.claude/projects/*/memory/task-queue.md
|
||||
|
||||
# Task format
|
||||
---
|
||||
name: task-queue
|
||||
type: project
|
||||
description: Persistent task queue for autonomous operation
|
||||
---
|
||||
|
||||
## Active Tasks
|
||||
- [ ] PR #123: Review and approve if CI green
|
||||
- [ ] Monitor deploy: check /health every 30 min for 2 hours
|
||||
- [ ] Research: Find 5 leads in AI tooling space
|
||||
|
||||
## Completed
|
||||
- [x] Daily standup: reviewed 3 PRs, 2 issues
|
||||
```
|
||||
|
||||
## Replacing Hermes
|
||||
|
||||
| Hermes Component | ECC Equivalent | How |
|
||||
|------------------|---------------|-----|
|
||||
| Gateway/Router | Claude Code dispatch + crons | Scheduled tasks trigger agent sessions |
|
||||
| Memory System | Claude memory + MCP memory server | Built-in persistence + knowledge graph |
|
||||
| Tool Registry | MCP servers | Dynamically loaded tool providers |
|
||||
| Orchestration | ECC skills + agents | Skill definitions direct agent behavior |
|
||||
| Computer Use | computer-use MCP | Native browser and desktop control |
|
||||
| Context Manager | Session management + memory | ECC 2.0 session lifecycle |
|
||||
| Task Queue | Memory-persisted task list | TodoWrite + memory files |
|
||||
|
||||
## Setup Guide
|
||||
|
||||
### Step 1: Configure MCP Servers
|
||||
|
||||
Ensure these are in `~/.claude.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"memory": {
|
||||
"command": "npx",
|
||||
"args": ["-y", "@anthropic/memory-mcp-server"]
|
||||
},
|
||||
"scheduled-tasks": {
|
||||
"command": "npx",
|
||||
"args": ["-y", "@anthropic/scheduled-tasks-mcp-server"]
|
||||
},
|
||||
"computer-use": {
|
||||
"command": "npx",
|
||||
"args": ["-y", "@anthropic/computer-use-mcp-server"]
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Step 2: Create Base Crons
|
||||
|
||||
```bash
|
||||
# Daily morning briefing
|
||||
claude -p "Create a scheduled task: every weekday at 9am, review my GitHub notifications, open PRs, and calendar. Write a morning briefing to memory."
|
||||
|
||||
# Continuous learning
|
||||
claude -p "Create a scheduled task: every Sunday at 8pm, extract patterns from this week's sessions and update the learned skills."
|
||||
```
|
||||
|
||||
### Step 3: Initialize Memory Graph
|
||||
|
||||
```bash
|
||||
# Bootstrap your identity and context
|
||||
claude -p "Create memory entities for: me (user profile), my projects, my key contacts. Add observations about current priorities."
|
||||
```
|
||||
|
||||
### Step 4: Enable Computer Use (Optional)
|
||||
|
||||
Grant computer-use MCP the necessary permissions for browser and desktop control.
|
||||
|
||||
## Example Workflows
|
||||
|
||||
### Autonomous PR Reviewer
|
||||
```
|
||||
Cron: every 30 min during work hours
|
||||
1. Check for new PRs on watched repos
|
||||
2. For each new PR:
|
||||
- Pull branch locally
|
||||
- Run tests
|
||||
- Review changes with code-reviewer agent
|
||||
- Post review comments via GitHub MCP
|
||||
3. Update memory with review status
|
||||
```
|
||||
|
||||
### Personal Research Agent
|
||||
```
|
||||
Cron: daily at 6 AM
|
||||
1. Check saved search queries in memory
|
||||
2. Run Exa searches for each query
|
||||
3. Summarize new findings
|
||||
4. Compare against yesterday's results
|
||||
5. Write digest to memory
|
||||
6. Flag high-priority items for morning review
|
||||
```
|
||||
|
||||
### Meeting Prep Agent
|
||||
```
|
||||
Trigger: 30 min before each calendar event
|
||||
1. Read calendar event details
|
||||
2. Search memory for context on attendees
|
||||
3. Pull recent email/Slack threads with attendees
|
||||
4. Prepare talking points and agenda suggestions
|
||||
5. Write prep doc to memory
|
||||
```
|
||||
|
||||
## Constraints
|
||||
|
||||
- Cron tasks run in isolated sessions — they don't share context with interactive sessions unless through memory.
|
||||
- Computer use requires explicit permission grants. Don't assume access.
|
||||
- Remote dispatch may have rate limits. Design crons with appropriate intervals.
|
||||
- Memory files should be kept concise. Archive old data rather than letting files grow unbounded.
|
||||
- Always verify that scheduled tasks completed successfully. Add error handling to cron prompts.
|
||||
@@ -1,222 +0,0 @@
|
||||
---
|
||||
name: lead-intelligence
|
||||
description: AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, and personalized outreach. Use when the user wants to find, qualify, and reach high-value contacts.
|
||||
origin: ECC
|
||||
---
|
||||
|
||||
# Lead Intelligence
|
||||
|
||||
Agent-powered lead intelligence pipeline that finds, scores, and reaches high-value contacts through social graph analysis and warm path discovery.
|
||||
|
||||
## When to Activate
|
||||
|
||||
- User wants to find leads or prospects in a specific industry
|
||||
- Building an outreach list for partnerships, sales, or fundraising
|
||||
- Researching who to reach out to and the best path to reach them
|
||||
- User says "find leads", "outreach list", "who should I reach out to", "warm intros"
|
||||
- Needs to score or rank a list of contacts by relevance
|
||||
- Wants to map mutual connections to find warm introduction paths
|
||||
|
||||
## Tool Requirements
|
||||
|
||||
### Required
|
||||
- **Exa MCP** — Deep web search for people, companies, and signals (`web_search_exa`)
|
||||
- **X API** — Follower/following graph, mutual analysis, recent activity (`X_BEARER_TOKEN`, `X_ACCESS_TOKEN`)
|
||||
|
||||
### Optional (enhance results)
|
||||
- **LinkedIn** — Via browser-use MCP or direct API for connection graph
|
||||
- **Apollo/Clay API** — For enrichment cross-reference if user has access
|
||||
- **GitHub MCP** — For developer-centric lead qualification
|
||||
|
||||
## Pipeline Overview
|
||||
|
||||
```
|
||||
┌─────────────┐ ┌──────────────┐ ┌─────────────────┐ ┌──────────────┐ ┌─────────────────┐
|
||||
│ 1. Signal │────▶│ 2. Mutual │────▶│ 3. Warm Path │────▶│ 4. Enrich │────▶│ 5. Outreach │
|
||||
│ Scoring │ │ Ranking │ │ Discovery │ │ │ │ Draft │
|
||||
└─────────────┘ └──────────────┘ └─────────────────┘ └──────────────┘ └─────────────────┘
|
||||
```
|
||||
|
||||
## Stage 1: Signal Scoring
|
||||
|
||||
Search for high-signal people in target verticals. Assign a weight to each based on:
|
||||
|
||||
| Signal | Weight | Source |
|
||||
|--------|--------|--------|
|
||||
| Role/title alignment | 30% | Exa, LinkedIn |
|
||||
| Industry match | 25% | Exa company search |
|
||||
| Recent activity on topic | 20% | X API search, Exa |
|
||||
| Follower count / influence | 10% | X API |
|
||||
| Location proximity | 10% | Exa, LinkedIn |
|
||||
| Engagement with your content | 5% | X API interactions |
|
||||
|
||||
### Signal Search Approach
|
||||
|
||||
```python
|
||||
# Step 1: Define target parameters
|
||||
target_verticals = ["prediction markets", "AI tooling", "developer tools"]
|
||||
target_roles = ["founder", "CEO", "CTO", "VP Engineering", "investor", "partner"]
|
||||
target_locations = ["San Francisco", "New York", "London", "remote"]
|
||||
|
||||
# Step 2: Exa deep search for people
|
||||
for vertical in target_verticals:
|
||||
results = web_search_exa(
|
||||
query=f"{vertical} {role} founder CEO",
|
||||
category="company",
|
||||
numResults=20
|
||||
)
|
||||
# Score each result
|
||||
|
||||
# Step 3: X API search for active voices
|
||||
x_search = search_recent_tweets(
|
||||
query="prediction markets OR AI tooling OR developer tools",
|
||||
max_results=100
|
||||
)
|
||||
# Extract and score unique authors
|
||||
```
|
||||
|
||||
## Stage 2: Mutual Ranking
|
||||
|
||||
For each scored target, analyze the user's social graph to find the warmest path.
|
||||
|
||||
### Algorithm
|
||||
|
||||
1. Pull user's X following list and LinkedIn connections
|
||||
2. For each high-signal target, check for shared connections
|
||||
3. Rank mutuals by:
|
||||
|
||||
| Factor | Weight |
|
||||
|--------|--------|
|
||||
| Number of connections to targets | 40% — highest weight, most connections = highest rank |
|
||||
| Mutual's current role/company | 20% — decision maker vs individual contributor |
|
||||
| Mutual's location | 15% — same city = easier intro |
|
||||
| Industry alignment | 15% — same vertical = natural intro |
|
||||
| Mutual's X handle / LinkedIn | 10% — identifiability for outreach |
|
||||
|
||||
### Output Format
|
||||
|
||||
```
|
||||
MUTUAL RANKING REPORT
|
||||
=====================
|
||||
|
||||
#1 @mutual_handle (Score: 92)
|
||||
Name: Jane Smith
|
||||
Role: Partner @ Acme Ventures
|
||||
Location: San Francisco
|
||||
Connections to targets: 7
|
||||
Connected to: @target1, @target2, @target3, @target4, @target5, @target6, @target7
|
||||
Best intro path: Jane invested in Target1's company
|
||||
|
||||
#2 @mutual_handle2 (Score: 85)
|
||||
...
|
||||
```
|
||||
|
||||
## Stage 3: Warm Path Discovery
|
||||
|
||||
For each target, find the shortest introduction chain:
|
||||
|
||||
```
|
||||
You ──[follows]──▶ Mutual A ──[invested in]──▶ Target Company
|
||||
You ──[follows]──▶ Mutual B ──[co-founded with]──▶ Target Person
|
||||
You ──[met at]──▶ Event ──[also attended]──▶ Target Person
|
||||
```
|
||||
|
||||
### Path Types (ordered by warmth)
|
||||
1. **Direct mutual** — You both follow/know the same person
|
||||
2. **Portfolio connection** — Mutual invested in or advises target's company
|
||||
3. **Co-worker/alumni** — Mutual worked at same company or attended same school
|
||||
4. **Event overlap** — Both attended same conference/program
|
||||
5. **Content engagement** — Target engaged with mutual's content or vice versa
|
||||
|
||||
## Stage 4: Enrichment
|
||||
|
||||
For each qualified lead, pull:
|
||||
|
||||
- Full name, current title, company
|
||||
- Company size, funding stage, recent news
|
||||
- Recent X posts (last 30 days) — topics, tone, interests
|
||||
- Mutual interests with user (shared follows, similar content)
|
||||
- Recent company events (product launch, funding round, hiring)
|
||||
|
||||
### Enrichment Sources
|
||||
- Exa: company data, news, blog posts
|
||||
- X API: recent tweets, bio, followers
|
||||
- GitHub: open source contributions (for developer-centric leads)
|
||||
- LinkedIn (via browser-use): full profile, experience, education
|
||||
|
||||
## Stage 5: Outreach Draft
|
||||
|
||||
Generate personalized outreach for each lead. Two modes:
|
||||
|
||||
### Warm Intro Request (to mutual)
|
||||
```
|
||||
hey [mutual name],
|
||||
|
||||
quick ask. i see you know [target name] at [company].
|
||||
i'm building [your product] which [1-line relevance to target].
|
||||
would you be open to a quick intro? happy to send you a
|
||||
forwardable blurb.
|
||||
|
||||
[your name]
|
||||
```
|
||||
|
||||
### Direct Cold Outreach (to target)
|
||||
```
|
||||
hey [target name],
|
||||
|
||||
[specific reference to their recent work/post/announcement].
|
||||
i'm [your name], building [product]. [1 line on why this is
|
||||
relevant to them specifically].
|
||||
|
||||
[specific low-friction ask].
|
||||
|
||||
[your name]
|
||||
```
|
||||
|
||||
### Anti-Patterns (never do)
|
||||
- Generic templates with no personalization
|
||||
- Long paragraphs explaining your whole company
|
||||
- Multiple asks in one message
|
||||
- Fake familiarity ("loved your recent talk!" without specifics)
|
||||
- Bulk-sent messages with visible merge fields
|
||||
|
||||
## Configuration
|
||||
|
||||
Users should set these environment variables:
|
||||
|
||||
```bash
|
||||
# Required
|
||||
export X_BEARER_TOKEN="..."
|
||||
export X_ACCESS_TOKEN="..."
|
||||
export X_ACCESS_TOKEN_SECRET="..."
|
||||
export X_API_KEY="..."
|
||||
export X_API_SECRET="..."
|
||||
export EXA_API_KEY="..."
|
||||
|
||||
# Optional
|
||||
export LINKEDIN_COOKIE="..." # For browser-use LinkedIn access
|
||||
export APOLLO_API_KEY="..." # For Apollo enrichment
|
||||
```
|
||||
|
||||
## Agents
|
||||
|
||||
This skill includes specialized agents in the `agents/` subdirectory:
|
||||
|
||||
- **signal-scorer** — Searches and ranks prospects by relevance signals
|
||||
- **mutual-mapper** — Maps social graph connections and finds warm paths
|
||||
- **enrichment-agent** — Pulls detailed profile and company data
|
||||
- **outreach-drafter** — Generates personalized messages
|
||||
|
||||
## Example Usage
|
||||
|
||||
```
|
||||
User: find me the top 20 people in prediction markets I should reach out to
|
||||
|
||||
Agent workflow:
|
||||
1. signal-scorer searches Exa and X for prediction market leaders
|
||||
2. mutual-mapper checks user's X graph for shared connections
|
||||
3. enrichment-agent pulls company data and recent activity
|
||||
4. outreach-drafter generates personalized messages for top ranked leads
|
||||
|
||||
Output: Ranked list with warm paths and draft outreach for each
|
||||
```
|
||||
@@ -1,85 +0,0 @@
|
||||
---
|
||||
name: enrichment-agent
|
||||
description: Pulls detailed profile, company, and activity data for qualified leads. Enriches prospects with recent news, funding data, content interests, and mutual overlap.
|
||||
tools:
|
||||
- Bash
|
||||
- Read
|
||||
- WebSearch
|
||||
- WebFetch
|
||||
model: sonnet
|
||||
---
|
||||
|
||||
# Enrichment Agent
|
||||
|
||||
You enrich qualified leads with detailed profile, company, and activity data.
|
||||
|
||||
## Task
|
||||
|
||||
Given a list of qualified prospects, pull comprehensive data from available sources to enable personalized outreach.
|
||||
|
||||
## Data Points to Collect
|
||||
|
||||
### Person
|
||||
- Full name, current title, company
|
||||
- X handle, LinkedIn URL, personal site
|
||||
- Recent posts (last 30 days) — topics, tone, key takes
|
||||
- Speaking engagements, podcast appearances
|
||||
- Open source contributions (if developer-centric)
|
||||
- Mutual interests with user (shared follows, similar content)
|
||||
|
||||
### Company
|
||||
- Company name, size, stage
|
||||
- Funding history (last round amount, investors)
|
||||
- Recent news (product launches, pivots, hiring)
|
||||
- Tech stack (if relevant)
|
||||
- Competitors and market position
|
||||
|
||||
### Activity Signals
|
||||
- Last X post date and topic
|
||||
- Recent blog posts or publications
|
||||
- Conference attendance
|
||||
- Job changes in last 6 months
|
||||
- Company milestones
|
||||
|
||||
## Enrichment Sources
|
||||
|
||||
1. **Exa** — Company data, news, blog posts, research
|
||||
2. **X API** — Recent tweets, bio, follower data
|
||||
3. **GitHub** — Open source profiles (if applicable)
|
||||
4. **Web** — Personal sites, company pages, press releases
|
||||
|
||||
## Output Format
|
||||
|
||||
```
|
||||
ENRICHED PROFILE: [Name]
|
||||
========================
|
||||
|
||||
Person:
|
||||
Title: [current role]
|
||||
Company: [company name]
|
||||
Location: [city]
|
||||
X: @[handle] ([follower count] followers)
|
||||
LinkedIn: [url]
|
||||
|
||||
Company Intel:
|
||||
Stage: [seed/A/B/growth/public]
|
||||
Last Funding: $[amount] ([date]) led by [investor]
|
||||
Headcount: ~[number]
|
||||
Recent News: [1-2 bullet points]
|
||||
|
||||
Recent Activity:
|
||||
- [date]: [tweet/post summary]
|
||||
- [date]: [tweet/post summary]
|
||||
- [date]: [tweet/post summary]
|
||||
|
||||
Personalization Hooks:
|
||||
- [specific thing to reference in outreach]
|
||||
- [shared interest or connection]
|
||||
- [recent event or announcement to congratulate]
|
||||
```
|
||||
|
||||
## Constraints
|
||||
|
||||
- Only report verified data. Do not hallucinate company details.
|
||||
- If data is unavailable, note it as "not found" rather than guessing.
|
||||
- Prioritize recency — stale data older than 6 months should be flagged.
|
||||
@@ -1,75 +0,0 @@
|
||||
---
|
||||
name: mutual-mapper
|
||||
description: Maps the user's social graph (X following, LinkedIn connections) against scored prospects to find mutual connections and rank them by introduction potential.
|
||||
tools:
|
||||
- Bash
|
||||
- Read
|
||||
- Grep
|
||||
- WebSearch
|
||||
- WebFetch
|
||||
model: sonnet
|
||||
---
|
||||
|
||||
# Mutual Mapper Agent
|
||||
|
||||
You map social graph connections between the user and scored prospects to find warm introduction paths.
|
||||
|
||||
## Task
|
||||
|
||||
Given a list of scored prospects and the user's social accounts, find mutual connections and rank them by introduction potential.
|
||||
|
||||
## Algorithm
|
||||
|
||||
1. Pull the user's X following list (via X API)
|
||||
2. For each prospect, check if any of the user's followings also follow or are followed by the prospect
|
||||
3. For each mutual found, assess the strength of the connection
|
||||
4. Rank mutuals by their ability to make a warm introduction
|
||||
|
||||
## Mutual Ranking Factors
|
||||
|
||||
| Factor | Weight | Assessment |
|
||||
|--------|--------|------------|
|
||||
| Connections to targets | 40% | How many of the scored prospects does this mutual know? |
|
||||
| Mutual's role/influence | 20% | Decision maker, investor, or connector? |
|
||||
| Location match | 15% | Same city as user or target? |
|
||||
| Industry alignment | 15% | Works in the target vertical? |
|
||||
| Identifiability | 10% | Has clear X handle, LinkedIn, email? |
|
||||
|
||||
## Warm Path Types
|
||||
|
||||
Classify each path by warmth:
|
||||
|
||||
1. **Direct mutual** (warmest) — Both user and target follow this person
|
||||
2. **Portfolio/advisory** — Mutual invested in or advises target's company
|
||||
3. **Co-worker/alumni** — Shared employer or educational institution
|
||||
4. **Event overlap** — Both attended same conference, accelerator, or program
|
||||
5. **Content engagement** — Target engaged with mutual's content recently
|
||||
|
||||
## Output Format
|
||||
|
||||
```
|
||||
WARM PATH REPORT
|
||||
================
|
||||
|
||||
Target: [prospect name] (@handle)
|
||||
Path 1 (warmth: direct mutual)
|
||||
Via: @mutual_handle (Jane Smith, Partner @ Acme Ventures)
|
||||
Relationship: Jane follows both you and the target
|
||||
Suggested approach: Ask Jane for intro
|
||||
|
||||
Path 2 (warmth: portfolio)
|
||||
Via: @mutual2 (Bob Jones, Angel Investor)
|
||||
Relationship: Bob invested in target's company Series A
|
||||
Suggested approach: Reference Bob's investment
|
||||
|
||||
MUTUAL LEADERBOARD
|
||||
==================
|
||||
#1 @mutual_a — connected to 7 targets (Score: 92)
|
||||
#2 @mutual_b — connected to 5 targets (Score: 85)
|
||||
```
|
||||
|
||||
## Constraints
|
||||
|
||||
- Only report connections you can verify from API data or public profiles.
|
||||
- Do not assume connections exist based on similar bios or locations alone.
|
||||
- Flag uncertain connections with a confidence level.
|
||||
@@ -1,98 +0,0 @@
|
||||
---
|
||||
name: outreach-drafter
|
||||
description: Generates personalized outreach messages for qualified leads. Creates warm intro requests, cold emails, X DMs, and follow-up sequences using enriched profile data.
|
||||
tools:
|
||||
- Read
|
||||
- Grep
|
||||
model: sonnet
|
||||
---
|
||||
|
||||
# Outreach Drafter Agent
|
||||
|
||||
You generate personalized outreach messages using enriched lead data.
|
||||
|
||||
## Task
|
||||
|
||||
Given enriched prospect profiles and warm path data, draft outreach messages that are short, specific, and actionable.
|
||||
|
||||
## Message Types
|
||||
|
||||
### 1. Warm Intro Request (to mutual)
|
||||
|
||||
Template structure:
|
||||
- Greeting (first name, casual)
|
||||
- The ask (1 sentence — can you intro me to [target])
|
||||
- Why it's relevant (1 sentence — what you're building and why target cares)
|
||||
- Offer to send forwardable blurb
|
||||
- Sign off
|
||||
|
||||
Max length: 60 words.
|
||||
|
||||
### 2. Cold Email (to target directly)
|
||||
|
||||
Template structure:
|
||||
- Subject: specific, under 8 words
|
||||
- Opener: reference something specific about them (recent post, announcement, thesis)
|
||||
- Pitch: what you do and why they specifically should care (2 sentences max)
|
||||
- Ask: one concrete low-friction next step
|
||||
- Sign off with one credibility anchor
|
||||
|
||||
Max length: 80 words.
|
||||
|
||||
### 3. X DM (to target)
|
||||
|
||||
Even shorter than email. 2-3 sentences max.
|
||||
- Reference a specific post or take of theirs
|
||||
- One line on why you're reaching out
|
||||
- Clear ask
|
||||
|
||||
Max length: 40 words.
|
||||
|
||||
### 4. Follow-Up Sequence
|
||||
|
||||
- Day 4-5: short follow-up with one new data point
|
||||
- Day 10-12: final follow-up with a clean close
|
||||
- No more than 3 total touches unless user specifies otherwise
|
||||
|
||||
## Writing Rules
|
||||
|
||||
1. **Personalize or don't send.** Every message must reference something specific to the recipient.
|
||||
2. **Short sentences.** No compound sentences with multiple clauses.
|
||||
3. **Lowercase casual.** Match modern professional communication style.
|
||||
4. **No AI slop.** Never use: "game-changer", "deep dive", "the key insight", "leverage", "synergy", "at the forefront of".
|
||||
5. **Data over adjectives.** Use specific numbers, names, and facts instead of generic praise.
|
||||
6. **One ask per message.** Never combine multiple requests.
|
||||
7. **No fake familiarity.** Don't say "loved your talk" unless you can cite which talk.
|
||||
|
||||
## Personalization Sources (from enrichment data)
|
||||
|
||||
Use these hooks in order of preference:
|
||||
1. Their recent post or take you genuinely agree with
|
||||
2. A mutual connection who can vouch
|
||||
3. Their company's recent milestone (funding, launch, hire)
|
||||
4. A specific piece of their thesis or writing
|
||||
5. Shared event attendance or community membership
|
||||
|
||||
## Output Format
|
||||
|
||||
```
|
||||
TO: [name] ([email or @handle])
|
||||
VIA: [direct / warm intro through @mutual]
|
||||
TYPE: [cold email / DM / intro request]
|
||||
|
||||
Subject: [if email]
|
||||
|
||||
[message body]
|
||||
|
||||
---
|
||||
Personalization notes:
|
||||
- Referenced: [what specific thing was used]
|
||||
- Warm path: [how connected]
|
||||
- Confidence: [high/medium/low]
|
||||
```
|
||||
|
||||
## Constraints
|
||||
|
||||
- Never generate messages that could be mistaken for spam.
|
||||
- Never include false claims about the user's product or traction.
|
||||
- If enrichment data is thin, flag the message as "needs manual personalization" rather than faking specifics.
|
||||
@@ -1,60 +0,0 @@
|
||||
---
|
||||
name: signal-scorer
|
||||
description: Searches and ranks prospects by relevance signals across X, Exa, and LinkedIn. Assigns weighted scores based on role, industry, activity, influence, and location.
|
||||
tools:
|
||||
- Bash
|
||||
- Read
|
||||
- Grep
|
||||
- Glob
|
||||
- WebSearch
|
||||
- WebFetch
|
||||
model: sonnet
|
||||
---
|
||||
|
||||
# Signal Scorer Agent
|
||||
|
||||
You are a lead intelligence agent that finds and scores high-value prospects.
|
||||
|
||||
## Task
|
||||
|
||||
Given target verticals, roles, and locations from the user, search for the highest-signal people using available tools.
|
||||
|
||||
## Scoring Rubric
|
||||
|
||||
| Signal | Weight | How to Assess |
|
||||
|--------|--------|---------------|
|
||||
| Role/title alignment | 30% | Is this person a decision maker in the target space? |
|
||||
| Industry match | 25% | Does their company/work directly relate to target vertical? |
|
||||
| Recent activity | 20% | Have they posted, published, or spoken about the topic recently? |
|
||||
| Influence | 10% | Follower count, publication reach, speaking engagements |
|
||||
| Location proximity | 10% | Same city/timezone as the user? |
|
||||
| Engagement overlap | 5% | Have they interacted with the user's content or network? |
|
||||
|
||||
## Search Strategy
|
||||
|
||||
1. Use Exa web search with category filters for company and person discovery
|
||||
2. Use X API search for active voices in the target verticals
|
||||
3. Cross-reference to deduplicate and merge profiles
|
||||
4. Score each prospect on the 0-100 scale using the rubric above
|
||||
5. Return the top N prospects sorted by score
|
||||
|
||||
## Output Format
|
||||
|
||||
Return a structured list:
|
||||
|
||||
```
|
||||
PROSPECT #1 (Score: 94)
|
||||
Name: [full name]
|
||||
Handle: @[x_handle]
|
||||
Role: [current title] @ [company]
|
||||
Location: [city]
|
||||
Industry: [vertical match]
|
||||
Recent Signal: [what they posted/did recently that's relevant]
|
||||
Score Breakdown: role=28/30, industry=24/25, activity=20/20, influence=8/10, location=10/10, engagement=4/5
|
||||
```
|
||||
|
||||
## Constraints
|
||||
|
||||
- Do not fabricate profile data. Only report what you can verify from search results.
|
||||
- If a person appears in multiple sources, merge into one entry.
|
||||
- Flag low-confidence scores where data is sparse.
|
||||
@@ -89,7 +89,7 @@ if (
|
||||
|
||||
const result = runCheck(root, ['--write']);
|
||||
assert.notStrictEqual(result.status, 0, result.stdout + result.stderr);
|
||||
assert.match(result.stderr, /scripts\/sample\.js:1:23 emoji U\+1F680/);
|
||||
assert.match(result.stderr, /scripts[/\\]sample\.js:1:23 emoji U\+1F680/);
|
||||
assert.strictEqual(fs.readFileSync(scriptFile, 'utf8'), original);
|
||||
})
|
||||
)
|
||||
|
||||
@@ -66,7 +66,11 @@ function makeHermeticCodexEnv(homeDir, codexDir, extraEnv = {}) {
|
||||
let passed = 0;
|
||||
let failed = 0;
|
||||
|
||||
if (
|
||||
// Windows NTFS does not allow double-quote characters in file paths,
|
||||
// so the quoted-path shell-injection test is only meaningful on Unix.
|
||||
if (os.platform() === 'win32') {
|
||||
console.log(' - install-global-git-hooks.sh quoted paths (skipped on Windows)');
|
||||
} else if (
|
||||
test('install-global-git-hooks.sh handles quoted hook paths without shell injection', () => {
|
||||
const homeDir = createTempDir('codex-hooks-home-');
|
||||
const weirdHooksDir = path.join(homeDir, 'git-hooks "quoted"');
|
||||
|
||||
@@ -30,6 +30,7 @@ function runGacha(pythonBin, arg) {
|
||||
return spawnSync(pythonBin, [SCRIPT, arg], {
|
||||
encoding: 'utf8',
|
||||
maxBuffer: 10 * 1024 * 1024,
|
||||
env: { ...process.env, PYTHONUTF8: '1' },
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user