lead-intelligence

lead-intelligence is a skill for Claude Code, Codex from hashgraph-online/awesome-codex-plugins. It costs 68 tokens per session (2,817 once invoked), scanned A, original, Apache-2.0.

A lead research and outreach workflow that finds potential contacts, ranks them, identifies shared connections, and helps prepare messages for email, LinkedIn, and X.

In plain words
What is it for?
Use it to build prospect lists for sales, partnerships, or fundraising; score contacts; find warm introduction paths; and prepare channel-specific outreach.
Why use it?
It reduces the manual work of deciding whom to contact, why they matter, and whether someone can introduce you. It uses public web and social-graph information to support that research.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to build prospect lists for sales, partnerships, or fundraising; score contacts; find warm introduction paths; and prepare channel-specific outreach.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hashgraph-online/awesome-codex-plugins/lead-intelligence
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add hashgraph-online/awesome-codex-plugins --skill lead-intelligence
Clone the repo
git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lead-intelligence

README.md
[![agentmods](https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence/github.svg)](https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence)
Your own site
<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for lead-intelligence

Your own site · 80×15
<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/lead-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,817 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.02817
Opus 5 $0.00034 $0.01409
Sonnet 5 $0.00014 $0.00563
Haiku 4.5 $0.00007 $0.00282

Measured 4d ago against content hash b03f936c816a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

lead-intelligence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

plugins/Colin4k1024/tsp/skills/lead-intelligence/SKILL.md · 346 lines

How it starts

The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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, plus write-context credentials such as X_CONSUMER_KEY, X_CONSUMER_SECRET, X_ACCESS_TOKEN, X_ACCESS_TOKEN_SECRET)

Optional (enhance results)

  • LinkedIn — Direct API if available, otherwise browser control for search, profile inspection, and drafting
  • Apollo/Clay API — For enrichment cross-reference if user has access
  • GitHub MCP — For developer-centric lead qualification
  • Apple Mail / Mail.app — Draft cold or warm email without sending automatically
  • Browser control — For LinkedIn and X when API coverage is missing or constrained

Pipeline Overview

┌─────────────┐     ┌──────────────┐     ┌─────────────────┐     ┌──────────────┐     ┌─────────────────┐
│ 1. Signal   │────>│ 2. Mutual    │────>│ 3. Warm Path    │────>│ 4. Enrich    │────>│ 5. Outreach     │
│    Scoring  │     │    Ranking   │     │    Discovery    │     │              │     │    Draft        │
└─────────────┘     └──────────────┘     └─────────────────┘     └──────────────┘     └─────────────────┘

Voice Before Outreach

Do not draft outbound from generic sales copy.

Run brand-voice first whenever the user's voice matters. Reuse its VOICE PROFILE instead of re-deriving style ad hoc inside this skill.

Read the full file on GitHub · 346 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 346 lines · 68 tokens per session scan A b03f936c816a

Subscribe to this mod's changes

lead-intelligence is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (956 stars, last pushed today), licensed Apache-2.0. It adds 68 tokens to every session and 2,817 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

Related

Other skills, from other repositories

search

Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.

taishi-i/awesome-ChatGPT-repositories · 57 tokens

sprr

Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".

wilsonfreitas/awesome-quant · 60 tokens

bprr

Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.

wilsonfreitas/awesome-quant · 61 tokens

drawio-reconstruction

Reconstructs reference images into high-fidelity, editable Draw.io files with rendered previews: native Draw.io elements carry text and structure, SVG covers simple icons that match the reference, and cropped or transparent PNGs preserve complex visuals. Use when the user wants a diagram image, research figure…

HKUSTDial/Supervisor-Skills · 102 tokens

benchmark-paper-template

Structures Benchmark and Evaluation papers using the five-pillar framework (Research Gap, Construction Pipeline, Evaluation Framework, Empirical Findings, optional Companion Method). Returns a completeness audit, a six-part Introduction logic chain, a Section 2-7 skeleton, and a pre-submission checklist. Use when…

HKUSTDial/Supervisor-Skills · 96 tokens

reverse-engineering-android-malware-with-jadx

Reverse engineers malicious Android APK files using JADX decompiler to analyze Java/Kotlin source code, identify malicious functionality including data theft, C2 communication, privilege escalation, and overlay attacks. Examines manifest permissions, receivers, services, and native libraries. Activates for requests…

adriannoes/awesome-agentic-ai · 82 tokens