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 bdfinst/agentic-dev-team --skill threat-modelinggit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWrote 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/bdfinst/agentic-dev-team/threat-modeling)<a href="https://agentmods.dev/skills/bdfinst/agentic-dev-team/threat-modeling"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/threat-modeling/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/bdfinst/agentic-dev-team/threat-modeling"><img src="https://agentmods.dev/badge/skills/bdfinst/agentic-dev-team/threat-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 33 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00051 | $0.01103 |
| Opus 5.5 | $0.00020 | $0.00441 |
| Sonnet 5.5 | $0.00010 | $0.00221 |
| Haiku 4.5 | $0.00005 | $0.00110 |
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 1mo 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling
Role: worker. This command performs STRIDE analysis directly and documents threats/mitigations — it does not implement the mitigations it identifies.
Overview
Structured security analysis for identifying threats, attack surfaces, and mitigations during design or review phases. Ensures security considerations are addressed before implementation, not after.
Constraints
- Focus on trust boundaries, not implementation details
- Every mitigation must map to a verifiable test or verification method
- Document accepted risks explicitly with rationale; do not silently ignore threats
- Revisit the threat model when architecture, authentication, or data flows change
Core Concepts
STRIDE Classification
| Category | Definition | Example Threats |
|---|---|---|
| Spoofing | Pretending to be something or someone else | Forged authentication tokens, impersonated services |
| Tampering | Modifying data or code without authorization | Altered request payloads, modified configuration files |
| Repudiation | Denying an action was performed | Unlogged administrative actions, unsigned transactions |
| Information Disclosure | Exposing data to unauthorized parties | Leaked credentials in logs, verbose error messages |
| Denial of Service | Making a system unavailable | Resource exhaustion, unbounded queries |
| Elevation of Privilege | Gaining access beyond authorization | Broken access control, privilege escalation via injection |
Trust Boundaries
Points where data crosses privilege levels. Every trust boundary is a potential attack surface. Common boundaries:
- Client to server
- Service to service (internal)
- Application to database
- System to external dependency
- User role transitions
Attack Surface
Entry points exposed to untrusted input: API endpoints, file uploads, message queues, configuration inputs, user-supplied queries. Smaller attack surface means fewer threats to mitigate.
Patterns
Threat Identification Procedure
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.
- 1mo ago First seen · 109 lines · 51 tokens per session scan A 9204bdd86d9f
threat-modeling is a skill published in the GitHub repository bdfinst/agentic-dev-team (295 stars, last pushed 4d ago), licensed MIT. It adds 51 tokens to every session and 1,103 once invoked, about $0.0002 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 2026-09-05.
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