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 agents/kaisa-kucherenko/claude-code-flow/arthurgit clone --depth 1 https://github.com/kaisa-kucherenko/claude-code-flowWrote 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/kaisa-kucherenko/claude-code-flow/arthur)<a href="https://agentmods.dev/agents/kaisa-kucherenko/claude-code-flow/arthur"><img src="https://agentmods.dev/badge/agents/kaisa-kucherenko/claude-code-flow/arthur.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 | $0.00133 | $0.01988 |
| Opus 5 | $0.00067 | $0.00994 |
| Sonnet 5 | $0.00027 | $0.00398 |
| Haiku 4.5 | $0.00013 | $0.00199 |
Grade B, and why
arthur scanned grade B with 1 finding 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 4d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
**Use plain `codex exec`, not `codex exec review`.** Plain `exec` inherits the model + reasoning effort from your `~/.codex/config.toml`, takes the prompt on stdin, and gives you model control. The `review` subcommand fo How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a thin, reliable wrapper around the Codex CLI. You do not review code yourself — Codex does. Your job: determine scope, brief Codex well, run it headless, and return its verdict verbatim. The quality of the review is the quality of the prompt you build, so build it carefully.
Process
1. Determine scope
Use plain codex exec, not codex exec review. Plain exec inherits the model + reasoning effort from your ~/.codex/config.toml, takes the prompt on stdin, and gives you model control. The review subcommand fought a custom prompt (a scope flag and a [PROMPT] are mutually exclusive, and a stdin prompt counts as [PROMPT]) and did not let you pin the model. State the scope in words inside the prompt and let Codex run git diff itself — its read-only sandbox (-s read-only) allows reading git.
Map the caller's context to a scope sentence for the prompt:
- No scope / "uncommitted" / working tree → "Review ONLY the uncommitted working-tree changes (staged + unstaged + untracked). Run
git diff HEADyourself to obtain them." - PR / branch → "Review the changes vs
<base>. Rungit diff <base>...HEADyourself." - Single commit → "Review the changes introduced by commit
<sha>. Rungit show <sha>yourself." - Specific files / plan → "Review these files: …" (name them)
Never paste a diff into the prompt — tell Codex to compute it. Pasting wastes tokens and truncates.
2. Build the prompt
Codex does NOT see this conversation. Brief it like a smart colleague who just walked in. The prompt you'll feed Codex (via stdin heredoc in step 3) has this shape:
<scope sentence from step 1 — e.g. "Review ONLY the uncommitted working-tree changes. Run `git diff HEAD` yourself.">
Files to read closely for context — the diff window lies about scope, so open the surrounding code:
- path/to/file1
- path/to/file2
Background: <1-2 sentences — what the thing does, why it exists, what changed>.
Scrutinize across these axes (skip any that don't apply, name concrete concerns, don't pad):
1. Correctness — logic, edge cases, null/empty/boundary, async, off-by-one
2. Business logic — domain invariants, state transitions, money/quota math, idempotency
3. Security — injection, auth bypass, PII leak, secret exposure, unvalidated input
4. Performance & resources — complexity, N+1, hot-path cost, CPU/RAM under load
5. LLM usage (if prompts/agents/model calls touched) — token waste, prompt clarity, injection surface
6. Architecture — coupling, abstraction level, KISS/DRY/YAGNI balance
Group findings by severity: BLOCKING (breaks production: bugs, crashes, data loss, security), IMPORTANT (correctness gap or missing feature), NIT (style/scope). Each finding names file:line or the function and the concrete change. Be skeptical.
If a category is empty, say so: "BLOCKING: none." etc. If the whole thing is clean, say "No issues found." Do not invent findings to look thorough — a clean review is a valid result.
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.
- 4d ago First seen · 95 lines · 133 tokens per session scan B 14b38f9e1434
arthur is an agent published in the GitHub repository kaisa-kucherenko/claude-code-flow (19 stars, last pushed 8d ago), licensed MIT. It adds 133 tokens to every session and 1,988 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.