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/halidsaglam/saglitzsecure/threat-modelingnpx skills add HalidSaglam/saglitzsecure --skill threat-modelinggit clone --depth 1 https://github.com/HalidSaglam/saglitzsecureWrote 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/halidsaglam/saglitzsecure/threat-modeling)<a href="https://agentmods.dev/skills/halidsaglam/saglitzsecure/threat-modeling"><img src="https://agentmods.dev/badge/skills/halidsaglam/saglitzsecure/threat-modeling.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 | $0.00060 | $0.01069 |
| Opus 5 | $0.00030 | $0.00535 |
| Sonnet 5 | $0.00012 | $0.00214 |
| Haiku 4.5 | $0.00006 | $0.00107 |
Grade A, and why
threat-modeling 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 5d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat modelling
This skill is not an audit but a frame: it settles what the system carries, who can attack it from where, and which target it should be designed against. It comes in before code is written or before an audit starts.
If the user is asking whether code that has been written is secure, the skill in play is security-audit, not this one; if they want the secure default for a specific decision (cookies, CORS, storing a secret) before writing code, secure-by-default is in play. This skill comes before both: it settles which asset matters and which boundary needs protecting, and the other two then work with that.
1. Call threat_model
Give the project's absolute root directory as path. The result carries:
assets— the valuable things the system holds (user accounts, server-side secrets, data stored on the device).trustBoundaries— the boundaries where one side does not trust the other (browser ↔ server, app ↔ network).attacker— the attacker types being modelled (an unauthenticated user, an authenticated but unauthorised user, someone who can read the repository).targetLevel— the suggested ASVS level.path— ordered steps to read, each tied to a knowledge section (knowledgeId) and to why it comes at that point in the order (why).
If the project type cannot be detected (kinds comes back empty) the tool still gives a
type-independent core model (secrets, authorization, dependencies); the notes field says that
this has to be completed by hand with the project's own assets and boundaries — do not skip that
note.
2. The level decision is the user's
The tool suggests L2 as the targetLevel because it cannot know the system's real value: L1 is
defensible only for low-risk applications that carry no data; L3 is for regulated or high-value
systems. Ask the user whether L1 or L3 fits better — they are the one who knows what the system
carries, who uses it and which regulation it falls under. Do not accept the tool's L2 without
question and make the decision on the user's behalf.
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.
- 5d ago First seen · 77 lines · 60 tokens per session scan A 6a01749aba67
threat-modeling is a skill published in the GitHub repository HalidSaglam/saglitzsecure (0 stars, last pushed 8d ago), licensed MIT. It adds 60 tokens to every session and 1,069 once invoked, about $0.0003 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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