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 almogdepaz/wolfpack --skill wolfpack-tailnet-controlgit clone --depth 1 https://github.com/almogdepaz/wolfpackWrote 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/almogdepaz/wolfpack/wolfpack-tailnet-control)<a href="https://agentmods.dev/skills/almogdepaz/wolfpack/wolfpack-tailnet-control"><img src="https://agentmods.dev/badge/skills/almogdepaz/wolfpack/wolfpack-tailnet-control/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/almogdepaz/wolfpack/wolfpack-tailnet-control"><img src="https://agentmods.dev/badge/skills/almogdepaz/wolfpack/wolfpack-tailnet-control.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.01824 |
| Opus 5.5 | $0.00012 | $0.00730 |
| Sonnet 5.5 | $0.00006 | $0.00365 |
| Haiku 4.5 | $0.00003 | $0.00182 |
Grade A, and why
wolfpack-tailnet-control scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 21d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wolfpack Session Control
Use the canonical CLI. Do not discover or reconstruct browser/private HTTP flows. Wolfpack uses its ordinary global API auth policy and adds no inter-session authorization layer.
Fast path
A top-level project session:
wolfpack session create <project> --harness <pi|claude|codex|gemini|cursor> --prompt '<instruction>' --json
A child of the current agent (same harness by default; full-startup assignment):
# Pi child: resolve the role model explicitly; use the reviewer setting for review.
IMPLEMENTER_MODEL="${WOLFPACK_IMPLEMENTER_MODEL:-openai-codex/gpt-6.1-sol:high}"
REVIEWER_MODEL="${WOLFPACK_REVIEWER_MODEL:-openai-codex/gpt-6.1-sol:high}"
wolfpack agent spawn <project> --harness pi --name 200-implementation --model "$IMPLEMENTER_MODEL" --plan .plans/000-task.md --notify-parent --json
# --model requires a pi child, not a pi parent. Omit it for other child harnesses.
wolfpack agent spawn <project> --harness claude --name 200-review --plan .plans/000-task.md --notify-parent --json
wolfpack session open is only a deprecated child-spawn alias. Never use it for a top-level request.
Replace <project> with --project-dir <path> when the user selects an existing directory outside the configured projects root; never pass both selectors. The CLI resolves relative paths and the server validates/canonicalizes the directory.
Both creation commands perform one server-owned request and pass startup instructions without inheriting parent transcript/context. --harness <pi|claude|codex|gemini|cursor> overrides the inherited child harness while preserving parent lineage; shell is not a child harness. --model is child-only and requires a Pi child; an explicit user/project model overrides the role environment/default.
Use --name <session> for child agents and choose a short meaningful issue/role slug, for example 200-implementation, 200-delivery-review, or auth-boundary-audit. Avoid generic *-sub-agent names when the task purpose is known; Wolfpack will allocate a numbered suffix if the requested name is already taken. Prefer --plan <file> for plan work: Wolfpack generates the compact handoff prompt and verifies the file exists without copying plan contents into the parent transcript. Use --prompt-file <file> for long bespoke instructions. Use raw --prompt only for one short prompt sentence. Do NOT paste repository policy, architecture context, or full plans into the launch command.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 21d ago Changed · +2 lines f75b56b3a685
- 22d ago Changed · +1 lines b21590f93430
- 25d ago Changed 4ce28482239a
- 1mo ago Changed · +3 lines bbef7f87e26e
- 2mo ago Changed · +5 lines e07e7d444fc9
- 2mo ago Changed · +11 lines 6a8aa8c2fdfd
- 2mo ago First seen · 61 lines · 31 tokens per session scan A d876a5c4176b
wolfpack-tailnet-control is a skill published in the GitHub repository almogdepaz/wolfpack (50 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 1,824 once invoked, about $0.0001 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 2026-08-30.
wolfpack-tailnet-control compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| wolfpack-tailnet-controlalmogdepaz/wolfpack | Skill | 50 | today | MIT | A | 31 | Claude Code, Codex |
| experiment-tracking-swanlabOrchestra-Research/AI-Research-SKILLs | Skill | 14k | 1mo ago | MIT | A | 40 | Claude Code, Codex |
| debugging-executionsn8n-io/n8n | Skill | 210k | today | none | A | 86 | Claude Code, Codex |
| suggest-automationsn8n-io/n8n | Skill | 210k | today | none | A | 87 | Claude Code, Codex |
| standardize-health-datathetahealth/mirobody | Skill | 1.4k | today | Apache-2.0 | A | 133 | Claude Code |
| pandic-officeTeam-Commonly/commonly | Skill | 1.4k | today | Apache-2.0 | A | 59 | Claude Code, Codex |
| apify-skillzeenie-ai/OpenCompany | Skill | 1.1k | today | MIT | A | 48 | Claude Code |