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 spiralcrew-ou/profilespider-agent-skills --skill territory-segmentationgit clone --depth 1 https://github.com/spiralcrew-ou/profilespider-agent-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/spiralcrew-ou/profilespider-agent-skills/territory-segmentation)<a href="https://agentmods.dev/skills/spiralcrew-ou/profilespider-agent-skills/territory-segmentation"><img src="https://agentmods.dev/badge/skills/spiralcrew-ou/profilespider-agent-skills/territory-segmentation/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/spiralcrew-ou/profilespider-agent-skills/territory-segmentation"><img src="https://agentmods.dev/badge/skills/spiralcrew-ou/profilespider-agent-skills/territory-segmentation.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 | $0.00038 | $0.00402 |
| Opus 5.5 | $0.00015 | $0.00161 |
| Sonnet 5.5 | $0.00008 | $0.00080 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
territory-segmentation 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 2mo 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.
What it actually says
Territory Segmentation
Purpose
Divide records into geographic or account-ownership territories with allocation notes.
When to use this skill
- Splitting a list across a sales team
- Applying geographic territory rules consistently
- Handling named-account ownership
- Auditing how accounts were allocated
When not to use this skill
- Records have no location or account-owner data
- You need balanced quota modeling (this assigns, not balances quotas)
- Ownership rules are undefined
Required inputs
- Records with location or account data
- Territory rules
Optional inputs
- Named-account ownership map
- Tie-break rules
- Region definitions
Rules
- Apply named-account ownership before geographic rules.
- Use only supplied location/account data.
- Flag records that cannot be resolved.
- Record the basis and any tie-breaks.
- Be consistent across records.
Process
- Parse territory and ownership rules.
- Apply named-account ownership.
- Assign remaining records geographically.
- Flag unresolved locations.
- Record allocation notes.
Output format
Return one assignment per record with the following fields:
- assigned_territory
- geographic_basis
- account_grouping
- unresolved_locations
- allocation_notes
Validation
- Confirm named accounts override geography.
- Confirm unresolved records are flagged, not guessed.
- Confirm the basis is recorded per record.
Limitations
- Assignment quality depends on location accuracy.
- It allocates by rules; it does not balance workloads.
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.
- 2mo ago First seen · 82 lines · 38 tokens per session scan A 9be7d1c22305
territory-segmentation is a skill published in the GitHub repository spiralcrew-ou/profilespider-agent-skills (11 stars, last pushed 4mo ago), licensed MIT. It adds 38 tokens to every session and 402 once invoked, about $0.0002 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 2026-08-31.
territory-segmentation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| territory-segmentationspiralcrew-ou/profilespider-agent-skills | Skill | 11 | 4mo ago | MIT | A | 38 | Claude Code, Codex |
| squeeze-page-builderAffitor/affiliate-skills | Skill | 767 | 18d ago | MIT | A | 114 | Claude Code |
| deepline-ads-audiencesgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 133 | Claude Code, Codex |
| deepline-enginegetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 43 | Claude Code, Codex |
| deepline-plays-reviewgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 121 | Codex |
| b2b-marketing-playbookGingiris-1031/gingiris-skills | Skill | 89 | 2d ago | MIT | A | 53 | Claude Code, Codex |
| deepline-crm-cleaninggetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 73 | Claude Code, Codex |