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 varunk130/ai-gtm-skill-library --skill territory-balancegit clone --depth 1 https://github.com/varunk130/ai-gtm-skill-libraryWrote 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/varunk130/ai-gtm-skill-library/territory-balance)<a href="https://agentmods.dev/skills/varunk130/ai-gtm-skill-library/territory-balance"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/territory-balance/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/varunk130/ai-gtm-skill-library/territory-balance"><img src="https://agentmods.dev/badge/skills/varunk130/ai-gtm-skill-library/territory-balance.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 | $0.00063 | $0.00678 |
| Opus 5.5 | $0.00025 | $0.00271 |
| Sonnet 5.5 | $0.00013 | $0.00136 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
territory-balance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 26d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Territory Balance (EVEN Framework)
Territories split by alphabet, zip code, or headcount look fair on a slide but drift out of balance within weeks. Territory Balance scores every account for near-term potential, then assigns accounts so each rep carries a comparable share of opportunity and a workload they can actually cover.
Core Principle
Balance opportunity and effort, not account count. Ten enterprise logos and ten small businesses are not the same book.
The EVEN Framework
| Letter | Step | The Question |
|---|---|---|
| E | Estimate | What is each account worth in the next 12 months? (whitespace × propensity) |
| V | Visit load | How many touches does each account need at its tier? |
| E | Equalize | Which assignment keeps every rep within ±10% of the mean potential and capacity? |
| N | Nudge | Which exceptions (existing relationships, language, time zone) justify breaking balance? |
Account potential = whitespace ($) × propensity (0-1), where propensity blends fit, intent, and engagement.
Rep load = Σ(touches per account per month) ÷ rep capacity (touches per month). Target 0.75-0.9.
Process
- Score accounts - compute potential; tier into A (top 20% of potential), B (next 30%), C (rest)
- Set touch norms - e.g. A = 8/month, B = 3/month, C = 1/month (pooled or digital-led)
- Assign greedily - hand out accounts in descending potential to the rep with the lowest current potential who still has capacity
- Apply exceptions - keep existing relationships where the account is mid-cycle; log every exception
- Check balance - report each rep's potential share and load; iterate until all fall in band
- Publish - territory list, balance table, and exception log
Output
Save to outputs/territory-balance-[period]-[YYYY-MM-DD].md
| Artifact | Description |
|---|---|
| Assignment table | Account, tier, potential, owner |
| Balance table | Rep, total potential, share vs mean, load |
| Exception log | Every manual override with its reason |
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.
- 26d ago First seen · 57 lines · 63 tokens per session scan A 2efc6ab0e67b
territory-balance is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 12d ago), licensed MIT. It adds 63 tokens to every session and 678 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-20.
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