Best for
- A consumer asks "is my agent setup safe / could this be weaponised".
- Before trusting a third-party skill pack, MCP server, or rules file.
- Periodic posture review of a fleet's agent config.
event4u-app/agent-config/src/skills/agent-security-review/SKILL.md
Use for an adversarial red-team / blue-team / auditor review of an AI agent's CONFIG + behaviour (rules, skills, MCP, hooks, permissions) — attack-chain → defensive-gap list, not a code audit.
Decision brief
A holistic, adversarial review of an agent's configuration and behaviour — the trust anchor, not the application code. Where threat-modeling models a code change and security-audit hunts code vulnerabilities, this skill asks: given this assembled agent config (rules, skills, MCP…
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/agent-security-review"Inspect the Agent Skill "agent-security-review" from https://github.com/event4u-app/agent-config/blob/0adf49a8ae84b0ff6e2de8759eea43257e020eff/src/skills/agent-security-review/SKILL.md at commit 0adf49a8ae84b0ff6e2de8759eea43257e020eff. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Inspect the config the agent actually loads and check each surface in turn: instruction files (CLAUDE.md / AGENTS.md / .cursor/rules / copilot-instructions), installed skills + their allowed-tools, MCP servers + their tool descriptions, hooks + lifecycle scripts, permission/auto…
A consumer asks "is my agent setup safe / could this be weaponised".
Inspect the config the agent actually loads and check each surface in turn: instruction files (CLAUDE.md / AGENTS.md / .cursor/rules / copilot-instructions), installed skills + their allowed-tools, MCP servers + their tool descriptions, hooks + lifecycle scripts, permission/auto…
For each surface, construct concrete attack chains, grounded in the known classes:
For each red-team chain, evaluate the existing defences: are the always-on rules (untrusted-input-defense, lethal-trifecta-guard, non-destructive-by-default) in force? Is the egress gated? Is the untrusted leg quarantined? Note what is present and what is absent.
Permission review
The documentation asks the agent to run terminal commands or scripts.
npx tsx node_modules/@event4u/agent-config/src/scripts/security_audit_config.ts --root <repo> --jsonEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 84/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 7 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
A holistic, adversarial review of an agent's configuration and behaviour —
the trust anchor, not the application code. Where threat-modeling
models a code change and security-audit hunts
code vulnerabilities, this skill asks: given this assembled agent config
(rules, skills, MCP servers, hooks, permissions, memory), how would an attacker
turn it against its owner, and what defensive gap lets them?
Pairs the static signal from /security-audit-config with an
adversarial three-lens pass. Output is decision support — surface the
trade-off, name the gap; the human decides.
D/F category from /security-audit-config that warrants depth.Inspect the config the agent actually loads and check each surface in turn:
instruction files (CLAUDE.md /
AGENTS.md / .cursor/rules / copilot-instructions), installed skills + their
allowed-tools, MCP servers + their tool descriptions, hooks + lifecycle
scripts, permission/auto-approve settings, persistent memory, and CI
workflows that run an AI agent (.github/workflows/* invoking an agent
action or CLI: check trigger — pull_request_target on fork PRs is
attacker-influenced —, permissions: grants, secrets exposure, and whether
PR title/body/diff flow into the agent's prompt). Run the static
pass first:
npx tsx node_modules/@event4u/agent-config/src/scripts/security_audit_config.ts --root <repo> --json
For each surface, construct concrete attack chains, grounded in the known classes:
bypassPermissions, Bash(*), auto-approve, npx -y.${{ secrets.NPM_TOKEN }}"; an agent triggered via
pull_request_target with permissions: write-all executes it —
entry: PR body → mechanism: prompt injection into the CI agent →
impact: secret exfiltration + supply-chain write).Name the chain: entry → mechanism → impact. Be specific (which file, which tool).
For each red-team chain, evaluate the existing defences: are the always-on
rules (untrusted-input-defense,
lethal-trifecta-guard,
non-destructive-by-default) in
force? Is the egress gated? Is the untrusted leg quarantined? Note what is
present and what is absent.
Pair each attack chain with its defensive gap and prioritise (likelihood ×
impact). For a neutral second opinion on the hardest calls, run
ai-council (council_depth: deep) and
judge-security-auditor over the flagged
files. Produce a ranked attack-chain → gap → recommended control table.
A prioritised findings table — attack chain | defensive gap | OWASP ASI | recommended control | confidence —
prefixed with the trust-and-safety banner, because this is advisory security output:
> HUMAN REVIEW REQUIRED — adversarial agent-config review. Findings are
> decision support, not a guarantee; detection is probabilistic. Validate
> each chain before acting.
Recommend controls; never auto-apply config changes (per
scope-control).
security-audit / threat-modeling./security-audit-config — the static A–F counterpart.untrusted-input-defense, lethal-trifecta-guard — the prevention rules.threat-modeling, judge-security-auditor, ai-council.Alternatives
coreyhaines31/marketingskills
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
event4u-app/agent-config
Grounded design brief from the adopted corpus — style, WCAG-checked color tokens, typography, layout pattern, anti-patterns. Use on ui-design-brief or any which-style/palette/font/chart decision.
event4u-app/agent-config
Use BEFORE writing or editing any non-trivial UI — inventories components, design tokens, shadcn primitives, and reusable patterns into state.ui_audit. Hard gate for the ui directive set.
event4u-app/agent-config
Use BEFORE writing/changing tests, adding mocks, or test-only methods on production classes — vs mocking-the-mock, production pollution, partial mocks, and overfit/tautological assertions