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 skills add guia-matthieu/clawfu-skills --skill lead-scoringgit clone --depth 1 https://github.com/guia-matthieu/clawfu-skillsWrote 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/guia-matthieu/clawfu-skills/lead-scoring)<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/lead-scoring"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/lead-scoring/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.
<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/lead-scoring"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/lead-scoring.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00025 | $0.02728 |
| Opus 5 | $0.00013 | $0.01364 |
| Sonnet 5 | $0.00005 | $0.00546 |
| Haiku 4.5 | $0.00003 | $0.00273 |
Grade A, and why
lead-scoring 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Scoring
Prioritize leads using a systematic scoring model that combines ICP fit, engagement behavior, and buying intent signals.
When to Use This Skill
- Designing a new lead scoring model
- Prioritizing inbound leads for SDR follow-up
- Setting MQL thresholds for sales handoff
- Analyzing lead quality by source
- Optimizing marketing spend by lead score
Methodology Foundation
Based on HubSpot's Lead Scoring methodology and Forrester's B2B Buyer Journey research, combining:
- Firmographic/demographic fit (who they are)
- Behavioral scoring (what they do)
- Intent signals (buying readiness)
- Negative scoring (disqualification)
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Designs scoring model structure | Point values for your business |
| Calculates lead scores | MQL threshold for handoff |
| Identifies high-intent behaviors | Which behaviors matter most |
| Segments leads by score | Sales follow-up priorities |
| Suggests model improvements | Model weight adjustments |
What This Skill Does
- Model design - Create scoring framework with fit + behavior + intent
- Score calculation - Apply model to lead data
- Threshold setting - Define MQL/SQL qualification levels
- Segmentation - Group leads by score for routing
- Optimization - Analyze score-to-conversion correlation
How to Use
For Model Design:
Help me create a lead scoring model for [Business Type].
Our ICP:
- Company size: [Range]
- Industries: [List]
- Titles: [Target titles]
- Geography: [Regions]
Key buying signals we track:
- [List website pages, content, actions]
Current conversion rates:
- Lead to MQL: X%
- MQL to SQL: X%
- SQL to Won: X%
For Lead Scoring:
Score this lead:
Company: [Name]
Size: [Employees]
Industry: [Industry]
Title: [Contact title]
Location: [Geography]
Behavior (last 30 days):
- [List pages visited, content downloaded, emails opened]
Instructions
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.
- 9d ago First seen · 418 lines · 25 tokens per session scan A 20ad3bf9b0c0
lead-scoring is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 2,728 once invoked, about $0.0001 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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