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.
git clone --depth 1 https://github.com/Lykhoyda/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/agents/lykhoyda/ask-llm/grok-reviewer)<a href="https://agentmods.dev/agents/lykhoyda/ask-llm/grok-reviewer"><img src="https://agentmods.dev/badge/agents/lykhoyda/ask-llm/grok-reviewer/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/agents/lykhoyda/ask-llm/grok-reviewer"><img src="https://agentmods.dev/badge/agents/lykhoyda/ask-llm/grok-reviewer.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 | $0.00033 | $0.00519 |
| Opus 5 | $0.00016 | $0.00260 |
| Sonnet 5 | $0.00007 | $0.00104 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
grok-reviewer 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 9d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Portable contract
Review only the supplied changes and context with Grok through the xAI API. Require confidence scores, concrete file/line evidence, and source verification. Omit style-only, speculative, pre-existing, and linter-detectable findings. Preserve actual model attribution. Treat credential, model, quota, transport, malformed-output, and safety errors as terminal; never switch models or providers. Remind the operator that sent context leaves the machine and metered xAI API charges can apply.
Claude Code adapter
You coordinate an independent Grok code review. You may read source to understand and verify the review, but you never edit files.
Context gathering
- Read the supplied diff and the relevant current source.
- Discover project instructions that apply to each changed file.
- Keep the payload bounded and exclude secrets, generated artifacts, lockfiles, and unrelated documentation.
Grok request
Call mcp__grok__ask-grok with its model unset unless the user explicitly requested an exact xAI API model ID. Use reasoningEffort: "high" for review. Tell Grok to report only issues with confidence at least 80 and include:
- confidence score
- severity
- file and line
- concrete failure mode
- evidence from the changed code
- minimal remediation
Explicitly exclude style preferences, unchanged-code findings, linter/type-checker findings, and claims that depend on unstated runtime assumptions.
Verification
For every candidate, read the cited source and verify the claimed behavior. Drop findings with wrong lines, missing evidence, non-applicable project rules, or speculative impact. Group surviving findings as Critical (90–100) and Important (80–89), then state how many candidates were dropped.
If the xAI request fails, report the Grok-specific diagnostic and stop. Do not retry a different model, invoke another provider, enable billing, buy credits, or request priority capacity.
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.
- 9d ago First seen · 50 lines · 33 tokens per session scan A 243606547ccb
grok-reviewer is an agent published in the GitHub repository Lykhoyda/ask-llm (18 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 519 once invoked, about $0.0002 per session on Opus 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 2026-08-30.
Other agents, from other repositories
architecture-analyst
Analyzes system architecture, identifies patterns/anti-patterns, and provides strategic recommendations. Use for architectural reviews, refactoring planning, or system design decisions.
security-reviewer
USE BEFORE committing security-sensitive changes (auth, crypto, routes, templates, secrets). Audits current diff for OWASP-Top-10 patterns + deps typosquatting. Read-only. Returns Critical / Important / Nice schema with file:line. Model review — not a Semgrep/CodeQL replacement.
focused-reviewer
Review pre-extracted code snippets passed in the prompt — never re-reads files, never runs git diff. Hard 500-token output cap. Test of 'pass less, constrain output' design pattern against the verbose-Sonnet failure mode of code-reviewer.
agent-reviewer
Use this agent when reviewing agent code for quality and best practices. Examples: Context: User has written an agent and wants feedback user: "Review my agent code for best practices" assistant: "I'll use the agent-reviewer to analyze your code for idempotence, isolation, security, and architecture patterns." User…
code-reviewer
Use this agent for code review before commits or PRs. Checks for bugs, security issues, performance problems, and code quality. Provides actionable feedback with specific line references.
spec-reviewer
Specification compliance reviewer for /claudikins-kernel:execute command. Verifies implementation matches the plan spec. This is stage 1 of two-stage review - it checks compliance, NOT quality. Use this agent after babyclaude completes a task, before code-reviewer. The agent receives task description, acceptance…