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 Frontal-so/outbound-skills --skill scoringgit clone --depth 1 https://github.com/Frontal-so/outbound-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/frontal-so/outbound-skills/scoring)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/scoring"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/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/frontal-so/outbound-skills/scoring"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/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 | $0.00113 | $0.01163 |
| Opus 5 | $0.00056 | $0.00581 |
| Sonnet 5 | $0.00023 | $0.00233 |
| Haiku 4.5 | $0.00011 | $0.00116 |
Grade A, and why
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 8d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lead Scoring
You help users build lead scoring systems in Clay using formulas and enrichment data to prioritize outreach.
Reference
Read {SKILL_BASE}/resources/templates/clay-enrichment-workflows.md for the scoring framework (Step 8 of the 9-step pipeline).
100-Point Scoring Model
| Component | Points | What It Measures |
|---|---|---|
| Company size match | 25 pts | Employee count fits ICP range |
| Recent signals | 25 pts | Job changes, funding, hiring, tech adoption |
| Email deliverability | 25 pts | Valid email, low bounce risk |
| ICP fit | 25 pts | Industry, revenue, tech stack match |
Tier Assignment
| Tier | Score | Action |
|---|---|---|
| Tier 1 | 80-100 | Immediate outreach, phone + email |
| Tier 2 | 60-79 | Nurture sequence, email only |
| Tier 3 | <60 | Long-term nurture or discard |
Building the Score in Clay
Use formula columns (0 credits) to calculate each component:
// Company size score (25 pts)
let sizeScore = 0;
let emp = {{employee_count}} || 0;
if (emp >= 50 && emp <= 500) sizeScore = 25; // Sweet spot
else if (emp >= 20 && emp < 50) sizeScore = 15; // Acceptable
else if (emp > 500 && emp <= 2000) sizeScore = 15; // Acceptable
else sizeScore = 5; // Poor fit
// ICP fit score (25 pts)
let icpScore = 0;
if ({{industry}} == "SaaS" || {{industry}} == "Software") icpScore += 15;
if ({{revenue}} > 5000000) icpScore += 10;
// Signal score (25 pts)
let signalScore = 0;
if ({{recent_funding}} && {{recent_funding}} != "purple") signalScore += 10;
if ({{job_change_90d}} == "true") signalScore += 10;
if ({{hiring_signals}} == "true") signalScore += 5;
// Deliverability score (25 pts)
let delivScore = 0;
if ({{email_validation}} == "valid") delivScore = 25;
else if ({{email_validation}} == "catchall valid") delivScore = 15;
else delivScore = 0;
// Total
sizeScore + icpScore + signalScore + delivScore
Segmentation Formula (Tier Assignment)
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.
- 8d ago First seen · 104 lines · 113 tokens per session scan A 8cc2274b669c
scoring is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 113 tokens to every session and 1,163 once invoked, about $0.0006 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 2026-08-31.
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