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 persona-mappinggit 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/persona-mapping)<a href="https://agentmods.dev/skills/frontal-so/outbound-skills/persona-mapping"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/persona-mapping/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/persona-mapping"><img src="https://agentmods.dev/badge/skills/frontal-so/outbound-skills/persona-mapping.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 | $0.00138 | $0.00700 |
| Opus 5 | $0.00069 | $0.00350 |
| Sonnet 5 | $0.00028 | $0.00140 |
| Haiku 4.5 | $0.00014 | $0.00070 |
Grade A, and why
persona-mapping 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 12d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona Mapping
You help users identify, segment, and target personas within accounts — mapping who to reach, what they care about, and how messaging differs.
Reference
Read {SKILL_BASE}/resources/abm/persona-mapping-framework.md for the complete framework.
Buying Committee Roles
| Role | Function | Budget Priority |
|---|---|---|
| Champion | Internal advocate who drives evaluation | 40-50% |
| Economic Buyer | Signs the check, cares about ROI | 20-30% |
| End User | Daily user, cares about UX/workflow | 15-20% |
| Technical Evaluator | Assesses integration, security, compliance | 5-10% |
| Blocker/Gatekeeper | Can veto but rarely initiates | Monitor only |
Persona Attributes to Capture
For each persona, define:
- Title patterns and seniority
- Function/department
- Jobs-to-be-done (JTBD)
- Pain points
- Success metrics
- Content preferences
- Buying role
LinkedIn Targeting Approaches
- Approach 1: Contact list upload — precise but expensive, 30-70% match rate
- Approach 2 (recommended): Company list + native LinkedIn filters — cheaper, 95-100% match rate
Campaign Naming Convention
[Campaign Name] - [Persona] - [Ad Type] - [JTBD/Intent] - [ABM Stage]
Example: Analytics-CMO-SingleImage-Attribution-Aware
Messaging Matrix
Each persona needs:
- Different JTBDs highlighted
- Different pain points addressed
- Stage-appropriate content (awareness vs consideration)
- Role-appropriate CTA (champion gets demo, end user gets trial)
Examples
Example 1: "Who should I target at my ABM accounts?" → Read persona-mapping-framework.md. Map buying committee: start with Champions (40-50% budget), then Economic Buyers (20-30%).
Example 2: "How do I tailor messaging for different personas?" → Build messaging matrix: different JTBD, pain points, and CTAs per persona. Champion gets ROI narrative, End User gets ease-of-use.
Example 3: "How should I name my campaigns for persona tracking?" → Use naming convention: [Campaign]-[Persona]-[AdType]-[JTBD]-[Stage]. Enables intent detection from campaign engagement data.
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.
- 12d ago First seen · 69 lines · 138 tokens per session scan A e2472d678a17
persona-mapping is a skill published in the GitHub repository Frontal-so/outbound-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 138 tokens to every session and 700 once invoked, about $0.0007 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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