Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.
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 foryourhealth111-pixel/Vibe-Skills --skill security-threat-modelgit clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-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/foryourhealth111-pixel/vibe-skills/security-threat-model)<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/security-threat-model"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/security-threat-model/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/foryourhealth111-pixel/vibe-skills/security-threat-model"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/security-threat-model.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 | $0.00082 | $0.01108 |
| Opus 5 | $0.00041 | $0.00554 |
| Sonnet 5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
Grade A, and why
security-threat-model 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 9d 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.
This is a copy
100% identical to security-threat-model — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model Source Code Repo
Deliver an actionable AppSec-grade threat model that is specific to the repository or a project path, not a generic checklist. Anchor every architectural claim to evidence in the repo and keep assumptions explicit. Prioritizing realistic attacker goals and concrete impacts over generic checklists.
Quick start
- Collect (or infer) inputs:
- Repo root path and any in-scope paths.
- Intended usage, deployment model, internet exposure, and auth expectations (if known).
- Any existing repository summary or architecture spec.
- Use prompts in
references/prompt-template.mdto generate a repository summary. - Follow the required output contract in
references/prompt-template.md. Use it verbatim when possible.
Workflow
1) Scope and extract the system model
- Identify primary components, data stores, and external integrations from the repo summary.
- Identify how the system runs (server, CLI, library, worker) and its entrypoints.
- Separate runtime behavior from CI/build/dev tooling and from tests/examples.
- Map the in-scope locations to those components and exclude out-of-scope items explicitly.
- Do not claim components, flows, or controls without evidence.
2) Derive boundaries, assets, and entry points
- Enumerate trust boundaries as concrete edges between components, noting protocol, auth, encryption, validation, and rate limiting.
- List assets that drive risk (data, credentials, models, config, compute resources, audit logs).
- Identify entry points (endpoints, upload surfaces, parsers/decoders, job triggers, admin tooling, logging/error sinks).
3) Calibrate assets and attacker capabilities
- List the assets that drive risk (credentials, PII, integrity-critical state, availability-critical components, build artifacts).
- Describe realistic attacker capabilities based on exposure and intended usage.
- Explicitly note non-capabilities to avoid inflated severity.
4) Enumerate threats as abuse paths
- Prefer attacker goals that map to assets and boundaries (exfiltration, privilege escalation, integrity compromise, denial of service).
- Classify each threat and tie it to impacted assets.
- Keep the number of threats small but high quality.
What ships with it
4 files 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.
- 9d ago First seen · 82 lines · 82 tokens per session scan A 1283c0dd62a8
security-threat-model is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,252 stars, last pushed 12d ago), licensed Apache-2.0. It adds 82 tokens to every session and 1,108 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-threat-model, differing in 0 lines, and is treated as a copy.
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