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 agentmods add skills/luisalima/agent-policy-kit/threat-modelnpx skills add luisalima/agent-policy-kit --skill threat-modelgit clone --depth 1 https://github.com/luisalima/agent-policy-kitWrote 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/luisalima/agent-policy-kit/threat-model)<a href="https://agentmods.dev/skills/luisalima/agent-policy-kit/threat-model"><img src="https://agentmods.dev/badge/skills/luisalima/agent-policy-kit/threat-model.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00593 |
| Opus 5 | $0.00014 | $0.00296 |
| Sonnet 5 | $0.00006 | $0.00119 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
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 6d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model
Use this skill before architecture work, especially before costly or hard-to-reverse decisions that introduce or change trust boundaries, auth, authorization, privileged automation, network exposure, data flows, multi-tenancy, deployment topology, secrets handling, or third-party integrations.
Do not make this a ritual for every task. State why threat modeling is relevant, and let the user decline unless the repo policy makes it a gate.
Goal
Produce an actionable AppSec threat model before the architecture becomes expensive to change.
Workflow
- Define scope: repo root, in-scope paths, deployment model, intended users, internet exposure, auth expectations, and sensitive data.
- Ground the system model in repository evidence. Identify runtime components, entry points, data stores, external integrations, CI/build tooling, and tests separately.
- Enumerate trust boundaries as concrete edges between components. Note protocol, auth, encryption, validation, authorization, and rate limiting when there is evidence.
- List assets that drive risk: credentials, PII, customer data, integrity critical state, build artifacts, release permissions, models, config, compute resources, and audit logs.
- State realistic attacker capabilities and non-capabilities. Avoid inflated threat assumptions.
- Enumerate a small set of abuse paths tied to assets and boundaries.
- Prioritize each threat with likelihood, impact, existing controls, and the assumptions that most affect the ranking.
- Ask 1-3 targeted questions if missing context materially changes the threat ranking. If the user cannot answer, record the assumption.
- Recommend concrete mitigations tied to locations, components, or boundaries.
Output
# Threat Model: <system or path>
## Scope
<in-scope and out-of-scope areas>
## System Model
<components, entry points, data stores, integrations, evidence>
## Trust Boundaries
- <boundary>: <protocol/auth/data/control notes>
## Assets
- <asset>: <why it matters>
## Attacker Capabilities
<capabilities and non-capabilities>
## Threats
### T1. <abuse path>
- Asset: <asset>
- Boundary: <boundary>
- Likelihood: Low | Medium | High
- Impact: Low | Medium | High
- Priority: Low | Medium | High | Critical
- Existing controls: <evidence-backed controls>
- Recommended mitigations: <specific actions>
## Assumptions And Open Questions
- <assumption or question>
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.
- 6d ago First seen · 80 lines · 28 tokens per session scan A a960dbef69e5
threat-model is a skill published in the GitHub repository luisalima/agent-policy-kit (2 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 593 once invoked, about $0.0001 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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