evaluating-model-guardrails SKILL.md skillA
evaluating-model-guardrails from unboundcompute/security-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add unboundcompute/security-agent-skills/evaluating-model-guardrails@git:20260816.a0bc1d1Pins git:20260816.a0bc1d1 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- unboundcompute/security-agent-skills
- Path
skills/evaluating-model-guardrails/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260816.a0bc1d1, committed Aug 16, 2026
- Size
- 6,881 bytes
- Repository stars
- 26
- License
- MIT
Systematically test whether a model's safety and policy guardrails hold under adversarial pressure, as a repeatable evaluation rather than a one-off trick. Covers building a policy-grounded probe set, multi-turn escalation, encoding and obfuscation bypasses, role and context reframing, instruction-hierarchy conflicts, and measuring bypass rate with reproducible graded outcomes. Use when reviewing a model deployment, a system prompt, or a content-safety layer, or before shipping an assistant…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Evaluating model guardrails: measure the boundary, don't collect one jailbreak A guardrail is a claim: "the model will refuse this class of request." A single successful jailbreak is an anecdote; what you need is a measurement, the rate at which the boundary holds across a structured battery of attacks. Evaluating guardrails means grounding probes in the actual policy, attacking each along known bypass axes, and scoring outcomes reproducibly, so you can state how strong the boundary is, not just that someone once beat it. ## When to use - You are reviewing a model deployment, a system prompt, or a content-safety layer. - Before shipping an assistant that must refuse or constrain a defined set of requests. - You need a defensible bypass rate, not a single proof-of-concept transcript. ## Scope check Evaluate models and deployments you own or are authorized to test. Use benign, clearly-scoped probes against a defined policy; do not generate real harmful output against systems you do not control. If you can't name the authorization, stop. ## The loop 1. **Ground the probes in the stated policy.** Get the actual list of what this …
Read the whole file at its exact version.
How to install
mdr add unboundcompute/security-agent-skills/evaluating-model-guardrails@sha256:3900aa4187fb53f7The line at the top of this page pins the label git:20260816.a0bc1d1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_qt2xjhwjdxnx46uv)
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Versions
The registry has recorded 1 version of this file, committed on Aug 16, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6881 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
unboundcompute/security-agent-skills · 26 stars · license MIT · pushed 2026-09-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_qt2xjhwjdxnx46uv GET https://markdownregistry.com/api/v1/resolve?ref=unboundcompute/security-agent-skills/evaluating-model-guardrails GET https://markdownregistry.com/api/v1/blob/3900aa4187fb53f7d545715ac3bb69690fcf5b8e8825753242d88831cbfd23d6
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.