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.
npx agentmods add skills/junmystery/agent-guidance-python/lead-intelligencenpx skills add JunMystery/Agent-Guidance-Python --skill lead-intelligencegit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWrote 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.
[](https://agentmods.dev/skills/junmystery/agent-guidance-python/lead-intelligence)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/lead-intelligence"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/lead-intelligence.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00068 | $0.02661 |
| Opus 5 | $0.00034 | $0.01331 |
| Sonnet 5 | $0.00014 | $0.00532 |
| Haiku 4.5 | $0.00007 | $0.00266 |
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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 322 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 asX_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.
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.
- today First seen · 322 lines · 68 tokens per session scan A 784d1f1d7303
lead-intelligence is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 2,661 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 2026-09-03.
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