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 euxx/claude-skills-for-copilot --skill security-threat-modelgit clone --depth 1 https://github.com/euxx/claude-skills-for-copilotWrote 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/euxx/claude-skills-for-copilot/security-threat-model)<a href="https://agentmods.dev/skills/euxx/claude-skills-for-copilot/security-threat-model"><img src="https://agentmods.dev/badge/skills/euxx/claude-skills-for-copilot/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/euxx/claude-skills-for-copilot/security-threat-model"><img src="https://agentmods.dev/badge/skills/euxx/claude-skills-for-copilot/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 | $0.01635 |
| Opus 5 | $0.00041 | $0.00817 |
| Sonnet 5 | $0.00016 | $0.00327 |
| Haiku 4.5 | $0.00008 | $0.00163 |
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 11d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Threat Model
Deliver an actionable AppSec-grade threat model specific to the repository or a project path. Anchor every architectural claim to evidence in the repo; keep assumptions explicit. Prioritize realistic attacker goals and concrete impacts over generic checklists.
Quality rules (apply throughout)
- Evidence-grounded: every component, data flow, or control must be backed by at least one repo path and, where helpful, a symbol name, config key, or short quoted snippet. Do not invent components.
- No secrets in output: if you find tokens, keys, or passwords, redact them and describe their presence and location only.
- Scope discipline: separate production/runtime behavior from CI/build/dev tooling and from tests/examples. Separate attacker-controlled inputs from operator-controlled and developer-controlled inputs.
- Concise for AppSec engineers: use precise terminology; include mitigations and residual risks; avoid restating large blocks of README/spec.
Workflow
1. Collect inputs
Ask the user (or infer and mark as assumptions):
- Intended usage and deployment model (server, CLI, library, worker)
- Internet exposure (public, internal, air-gapped)
- Authentication / authorization expectations
- Data sensitivity (PII, credentials, financial, public)
- Any explicitly out-of-scope paths
If the user provided a path argument, scope the model to that sub-path.
2. Explore the repo
Use file search, grep -rI (skip binaries), or ripgrep rg (skips binaries by
default) to locate security-relevant surfaces:
- Network listeners, routes, endpoints, RPC handlers, message consumers
- Auth, session/token handling, RBAC/ACL logic
- Parsing/deserialization (JSON/YAML/XML/protobuf), template rendering,
eval - File upload/read paths, archive extraction, image/document parsing
- Database, queue, and cache clients and query construction
- Secrets/config loading, environment variables, key management
- SSRF-capable HTTP clients, webhooks, URL fetchers
- Sandboxing, privilege boundaries, subprocess execution
- Logging/error handling paths
- CI/build pipelines, dependency management, artifact publishing
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.
- 11d ago First seen · 183 lines · 82 tokens per session scan A 409f95ea4273
security-threat-model is a skill published in the GitHub repository euxx/claude-skills-for-copilot (4 stars, last pushed 2mo ago), licensed MIT. It adds 82 tokens to every session and 1,635 once invoked, about $0.0004 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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release-jetbrains
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chart
Use when the user asks to visualize data with charts, graphs, or plots using the chart tool (bar, line, scatter, pie, time series, etc.).
gh-issues
Use when creating, triaging, or commenting on GitHub issues for the Kilo VS Code extension or JetBrains plugin via gh. Covers issue templates, project board assignment, title conventions, and required gh scopes.