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/cloudnative-co/claude-code-starter-kit/clickhouse-ionpx skills add cloudnative-co/claude-code-starter-kit --skill clickhouse-iogit clone --depth 1 https://github.com/cloudnative-co/claude-code-starter-kitWhat 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 | $0.00026 | $0.00415 |
| Opus 5 | $0.00013 | $0.00208 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
clickhouse-io 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 3d 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.
What it actually says
ClickHouse Analytics Patterns
ClickHouse is a column-oriented DBMS for OLAP, optimized for fast analytical queries on large datasets. Key strengths: columnar storage, compression, parallel execution, distributed queries, real-time analytics.
Reference Files
| File | Contents |
|---|---|
| references/table-design.md | MergeTree engine types, table creation patterns, partitioning, ordering keys, data type selection |
| references/query-optimization.md | Filtering best practices, aggregations, window functions, materialized views, performance monitoring |
| references/data-pipeline.md | Bulk/streaming insert, ETL/CDC patterns, time series, funnel, cohort, and retention query templates |
Engine Selection Guide
| Engine | Use When | Trade-off |
|---|---|---|
| MergeTree | Default for most tables | No dedup or pre-aggregation |
| ReplacingMergeTree | Data has duplicates from multiple sources | Dedup only on merge, not query time |
| AggregatingMergeTree | Pre-computed rollups (hourly/daily stats) | Requires *State/*Merge function pairs |
Core Rules
- Batch inserts -- never insert row-by-row
- Specify columns -- avoid
SELECT * - Filter on indexed columns first -- match ORDER BY key order
- Denormalize -- minimize JOINs for analytical tables
- Leverage materialized views -- for real-time aggregations
ClickHouse excels at analytical workloads. Design tables for your query patterns, batch inserts, and leverage materialized views for real-time aggregations.
What ships with it
3 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.
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.
- 3d ago First seen · 36 lines · 26 tokens per session scan A 2191873ebf1a
clickhouse-io is a skill published in the GitHub repository cloudnative-co/claude-code-starter-kit (147 stars, last pushed 10d ago), licensed MIT. It adds 26 tokens to every session and 415 once invoked, about $0.0001 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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