Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Lykhoyda/ask-llm/plugin install ask-llmWrote 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/lykhoyda/ask-llm/ask-llm-review)<a href="https://agentmods.dev/skills/lykhoyda/ask-llm/ask-llm-review"><img src="https://agentmods.dev/badge/skills/lykhoyda/ask-llm/ask-llm-review/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/lykhoyda/ask-llm/ask-llm-review"><img src="https://agentmods.dev/badge/skills/lykhoyda/ask-llm/ask-llm-review.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 | $0.00062 | $0.00789 |
| Opus 5.5 | $0.00025 | $0.00316 |
| Sonnet 5.5 | $0.00012 | $0.00158 |
| Haiku 4.5 | $0.00006 | $0.00079 |
Grade A, and why
ask-llm-review 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 14d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Portable contract
Gather the relevant staged, unstaged, and untracked code changes; build a bounded context brief; request a read-only Codex review at high reasoning effort; verify each reported finding against source; and return only prioritized, source-supported findings. Preserve the configured Sol-to-Terra fallback and disclose it.
Host adapters
Pi adapter
Call the native ask-codex tool with reasoningEffort: "high" and apply the portable contract above. The review runs inline in the current host context; do not claim subagent isolation.
Other hosts adapter
Codex, Cursor Agent, Antigravity, Grok Build, Gemini CLI and OpenCode get this skill from their skills folder, not from a plugin. Apply the portable contract above inline, with the Codex call from transport.md (next to this file): model: "gpt-6-astra", reasoningEffort: "high", sandbox: "read-only". There is no isolated reviewer subagent on these hosts; do not claim one.
Claude Code adapter
The existing detailed workflow below is the Claude Code adapter. Its Agent, MCP, hook, CLAUDE_PLUGIN_ROOT, and AskUserQuestion mechanics apply only on Claude Code; they do not override the Pi adapter above.
Codex Code Review
Review current code changes by delegating to the codex-reviewer agent.
When to use this vs codex-pair
This skill is precision-first: confidence ≥ 80, "don't flag style/linter-catchable" filter. Optimized for low false-alarm rate on diff review — appropriate default for routine PRs.
For recall-first review on hot-path code (money handling, security paths, spec-implementing code), see the codex-pair sibling — a PostToolUse hook that opts in per-project via a .codex-pair/context.md marker file. The 4-task benchmark in ADR-077 shows codex-pair catches domain-level "wrong but won't crash" issues (float-money precision, cross-cutting validation gaps, edge clamping) that this skill's confidence filter structurally suppresses. Different classes of bug, not the same class with different completeness.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 14d ago First seen · 57 lines · 62 tokens per session scan A e0da57d1728d
ask-llm-review is a skill published in the GitHub repository Lykhoyda/ask-llm (18 stars, last pushed 2d ago), licensed MIT. It adds 62 tokens to every session and 789 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 2026-10-03.
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