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 skills/nevaberry/nevaberry-plugins/clickhouse-knowledge-patchnpx skills add Nevaberry/nevaberry-plugins --skill clickhouse-knowledge-patchgit clone --depth 1 https://github.com/Nevaberry/nevaberry-pluginsWrote 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/nevaberry/nevaberry-plugins/clickhouse-knowledge-patch)<a href="https://agentmods.dev/skills/nevaberry/nevaberry-plugins/clickhouse-knowledge-patch"><img src="https://agentmods.dev/badge/skills/nevaberry/nevaberry-plugins/clickhouse-knowledge-patch.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 | $0.00009 | $0.02231 |
| Opus 5 | $0.00005 | $0.01115 |
| Sonnet 5 | $0.00002 | $0.00446 |
| Haiku 4.5 | $0.00001 | $0.00223 |
Grade A, and why
clickhouse-knowledge-patch 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 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.
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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ClickHouse Knowledge Patch
Use this skill when writing, reviewing, upgrading, or operating ClickHouse SQL and server configurations. Start with the compatibility-sensitive items below, then load the topic reference that matches the task.
How to apply this skill
- Inspect the target server version, table engines, client settings, and relevant feature flags before generating SQL.
- For upgrades, review changed defaults and removed compatibility paths before adopting new syntax.
- Treat experimental features as explicit opt-ins and keep their configuration easy to remove.
- For distributed or object-storage work, distinguish query settings, engine settings, server settings, named collections, and access-control grants.
- Validate optimizer choices with
EXPLAIN; do not assume a projection, index, cache, or parallel-replica path is selected merely because it exists. - Preserve operational safety around background work, credential inheritance, deduplication, and remote-query execution.
Reference index
| Reference | Topics |
|---|---|
| Upgrades, security, and settings | Credential inheritance, removed settings, deduplication migration, changed defaults, access changes, terminal output |
| Query language and functions | CTEs, EXPLAIN, time functions, aggregates, query parameters, dictionary lookup, hashing, JSON extraction |
| Tables, indexes, and views | MergeTree, projections, text and hypothetical indexes, semi-structured types, constraints, refresh chains |
| External data and formats | Object storage, lakehouse catalogs, URL dispatch, remote databases, Arrow Flight, GeoJSON, PNG |
| Operations, integrations, and tooling | Background controls, workloads, Kafka and NATS, Keeper, dictionaries, PromQL, local listeners, streaming |
| Vectors, geometry, and classifiers | QBit, quantization, Hadamard transforms, embedding generation, Naive Bayes, geometry and vector tiles |
What ships with it
7 files 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.
- coverage.json 487 B
- references/external-data-and-formats.md 5.9 KB
- references/operations-integrations-and-tooling.md 6.4 KB
- references/query-language-and-functions.md 6.5 KB
- references/tables-indexes-and-views.md 5.0 KB
- references/upgrades-security-and-settings.md 4.5 KB
- references/vectors-geometry-and-classifiers.md 4.6 KB
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 · 182 lines · 9 tokens per session scan A e7ef0770ca9a
clickhouse-knowledge-patch is a skill published in the GitHub repository Nevaberry/nevaberry-plugins (24 stars, last pushed 8d ago), licensed MIT. It adds 9 tokens to every session and 2,231 once invoked, about $0.0000 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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