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 commands/mturac/everything-openai-codex/security-scangit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/commands/mturac/everything-openai-codex/security-scan)<a href="https://agentmods.dev/commands/mturac/everything-openai-codex/security-scan"><img src="https://agentmods.dev/badge/commands/mturac/everything-openai-codex/security-scan.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 | $0.00016 | $0.00652 |
| Opus 5 | $0.00008 | $0.00326 |
| Sonnet 5 | $0.00003 | $0.00130 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
security-scan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to security-scan — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Scan Command
Run AgentShield against the current project or a target path, then turn the findings into a prioritized remediation plan.
Usage
/security-scan [path] [--format text|json|markdown|html] [--min-severity low|medium|high|critical] [--fix]
path(optional): defaults to the current project. Use a.codex/path, a repo root, or a checked-in template directory.--format: output format. Usejsonfor CI,markdownfor handoffs, andhtmlfor standalone review reports.--min-severity: filters lower-priority findings.--fix: applies only AgentShield fixes explicitly marked as safe and auto-fixable.
Deterministic Engine
Prefer the packaged scanner:
npx ecc-agentshield scan --path "${TARGET_PATH:-.}" --format text
For local AgentShield development, run from the AgentShield checkout:
npm run scan -- --path "${TARGET_PATH:-.}" --format text
Do not invent findings. Use AgentShield output as the source of truth and separate scanner facts from follow-up judgment.
Review Checklist
- Identify active runtime findings first:
- hardcoded secrets
- broad permissions
- executable hooks
- MCP servers with shell, filesystem, remote transport, or unpinned
npx - agent prompts that handle untrusted content without defenses
- Separate lower-confidence inventory:
- docs examples
- template examples
- plugin manifests
- project-local optional settings
- For each critical or high finding, return:
- file path
- severity
- runtime confidence
- why it matters
- exact remediation
- whether it is safe to auto-fix
- If
--fixis requested, state the planned edits before applying fixes. - Re-run the scan after fixes and report the before/after score.
Output Contract
Return:
- Security grade and score.
- Counts by severity and runtime confidence.
- Critical/high findings with exact paths.
- Lower-confidence findings grouped separately.
- A remediation order.
- Commands run and whether the scan was local, CI, or npx-backed.
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.
- 2d ago First seen · 93 lines · 16 tokens per session scan A 4a51953f94b5
security-scan is a command published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 12d ago), licensed MIT. It adds 16 tokens to every session and 652 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to security-scan, differing in 8 lines, and is treated as a copy.
Other commands, from other repositories
goal
Set a goal and enter the RALPH loop — keep working autonomously until the goal is genuinely done or the user stops you. Use /goal "objective" to start, /goal status to check, /goal complete to finish, /goal clear to stop.
teach
Hand-record a lesson into Memory Fabric (learning tier, high confidence) so it is recalled later.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.