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 qualify-accountsgit 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/qualify-accounts)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/qualify-accounts"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/qualify-accounts/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/qualify-accounts"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/qualify-accounts.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 | $0.00105 | $0.01099 |
| Opus 5 | $0.00053 | $0.00549 |
| Sonnet 5 | $0.00021 | $0.00220 |
| Haiku 4.5 | $0.00011 | $0.00110 |
Grade A, and why
qualify-accounts 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 11d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qualify Accounts — Sub-Skill
You help users score, qualify, and prioritize target accounts using ABM tier frameworks and intent data. Always read the reference file before responding.
Reference
Read {SKILL_BASE}/resources/sales-navigator-guide.md — sections: ICP Scoring, Scoring Matrix, ABM List Building, Intent Data Layering, Lookalike Building.
Read {SKILL_BASE}/resources/templates/qualification-workflow.md — Frontal tier system (Company/Contact tiers), weighted ICP scoring, Clay AI qualification prompts, real DevOps scoring examples, source comparison matrix, and "good list" column template.
ABM Tier Structure
| Tier | Accounts | Approach | Resources |
|---|---|---|---|
| Tier 1 (1:1) | 10-50 | Fully custom, multi-threaded | Maximum — custom content, executive outreach, direct mail |
| Tier 2 (1:Few) | 50-200 | Segment-based personalization | Medium — industry/persona templates, targeted ads |
| Tier 3 (1:Many) | 200-1,000 | Programmatic, automated | Low — automated sequences, broad messaging |
Account Scoring Process
- Apply ICP scoring matrix (100-point system from define-icp)
- Layer intent data to adjust scores dynamically
- Assign ABM tier based on final score
- Map contacts per account (Economic Buyer, Champion, Technical Evaluator, End User, Blocker, Coach)
Intent Data Layers
| Layer | Sources | Signal Strength |
|---|---|---|
| First-party | Website visits, pricing page views, content downloads, webinar attendance | Strongest |
| Second-party | G2 Buyer Intent, TrustRadius, Capterra reviews/comparisons | Strong |
| Third-party | Bombora, 6sense, ZoomInfo Intent, TechTarget | Moderate |
| LinkedIn-native | Buyer Intent signals, ad engagement, page followers | Moderate |
Scoring adjustment: Add 10-20 points for strong first-party intent. Add 5-10 for second/third-party. An account scoring 65 (Tier C) with strong first-party intent jumps to 75-85 (Tier B).
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.
- 11d ago First seen · 75 lines · 105 tokens per session scan A 59fe08980633
qualify-accounts is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 1,099 once invoked, about $0.0005 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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