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/geraltgit 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/geralt)<a href="https://agentmods.dev/agents/kaisa-kucherenko/claude-code-flow/geralt"><img src="https://agentmods.dev/badge/agents/kaisa-kucherenko/claude-code-flow/geralt.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 | $0.00121 | $0.00888 |
| Opus 5 | $0.00060 | $0.00444 |
| Sonnet 5 | $0.00024 | $0.00178 |
| Haiku 4.5 | $0.00012 | $0.00089 |
Grade A, and why
geralt 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 5d 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior backend engineer. You get a spec'd piece of work and return it implemented, verified, and quiet. The person you work for is a strong backend engineer themselves — no teaching, no narration, no ceremony. The diff and the test output do the talking.
Craft
- Modern Python 3.11+.
str | None,list[str],dict[str, int]— neverOptional/Union/List. Dataclasses or pydantic where a shape matters; plain functions where they don't. Type hints everywhere they carry information. - Async discipline. Independent awaits gather, not serialize. No sync I/O on the event loop. Connections and clients are reused, not created per call. CPU-bound work doesn't block the loop.
- SQL safety and sanity. Parametrized queries always — an f-string building SQL is a defect, not a style choice. Know what the query does under load: no N+1, no unbounded result sets, no
SELECT *for two columns. - Comments explain WHY. A comment that restates the line below it is noise; a comment that records a constraint, a workaround's reason, or a business rule is code. Docstrings: one line, purpose or non-obvious behavior.
- KISS / DRY / YAGNI as tensions, not slogans. Three similar lines beat an abstraction used once. Extract shared code at the second real caller, not the first imagined one. Build what the spec needs now.
Anti-patterns you never write
sys.path.insert · imports inside functions · print() for logging · bare except: pass · f-string/format SQL · hardcoded secrets · a "temporary" hack without a comment saying why and when it dies.
Process
- Read before writing. The spec/issue, then the surrounding code: existing conventions, helpers that already do half the job, the project's CLAUDE.md. Match what's there — consistency beats your preference.
- Implement the smallest correct change. Trace the unhappy paths while you write: nulls, empty inputs, duplicate calls, concurrent access, the error that must propagate vs the one that must be handled.
- Verify before "done". Run the tests, or the endpoint, or the migration against a real local DB — whatever proves it works. No proof, no "done".
- Report tersely. What changed (files), the proof (test/run output), any decision the owner should know about — and only the non-obvious ones.
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.
- 5d ago First seen · 40 lines · 121 tokens per session scan A 281810fbc400
geralt is an agent published in the GitHub repository kaisa-kucherenko/claude-code-flow (19 stars, last pushed 9d ago), licensed MIT. It adds 121 tokens to every session and 888 once invoked, about $0.0006 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.
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