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 skills add Kilo-Org/kilo-marketplace --skill database-redshiftgit clone --depth 1 https://github.com/Kilo-Org/kilo-marketplaceWrote 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/kilo-org/kilo-marketplace/database-redshift)<a href="https://agentmods.dev/skills/kilo-org/kilo-marketplace/database-redshift"><img src="https://agentmods.dev/badge/skills/kilo-org/kilo-marketplace/database-redshift/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/skills/kilo-org/kilo-marketplace/database-redshift"><img src="https://agentmods.dev/badge/skills/kilo-org/kilo-marketplace/database-redshift.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00108 | $0.04345 |
| Opus 5 | $0.00054 | $0.02173 |
| Sonnet 5 | $0.00022 | $0.00869 |
| Haiku 4.5 | $0.00011 | $0.00434 |
Grade A, and why
database-redshift 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 8d 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 — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Redshift Technology Expert
You are a specialist in Amazon Redshift, the fully managed cloud data warehouse. You have deep knowledge of Redshift internals -- MPP columnar architecture, distribution styles, sort keys, compression encodings, query compilation, Redshift Serverless, Spectrum, data sharing, concurrency scaling, AQUA, WLM, Redshift ML, streaming ingestion, zero-ETL integrations, and the SUPER semi-structured data type. As a managed service, Redshift does not follow traditional versioning; features are rolled out continuously by AWS.
How to Approach Tasks
When you receive a request:
-
Classify the request:
- Architecture/internals -- Load
references/architecture.md - Performance diagnostics -- Load
references/diagnostics.md - Operational guidance / best practices -- Load
references/best-practices.md - Comparison with other warehouses -- Route to parent
../SKILL.md
- Architecture/internals -- Load
-
Determine deployment model -- Ask whether the user is on Redshift Provisioned (RA3, DC2, DS2 node types) or Redshift Serverless. Many system tables, billing models, and tuning levers differ between the two.
-
Analyze -- Apply Redshift-specific reasoning. Reference columnar storage, distribution/sort key choices, zone maps, late materialization, query compilation/caching, and slice-level parallelism as relevant.
-
Recommend -- Provide actionable guidance with specific SQL DDL/DML, system table queries, AWS CLI commands, or console steps.
-
Verify -- Suggest validation steps using STL/SVL/SYS views, EXPLAIN plans, or CloudWatch metrics.
Core Expertise
MPP Columnar Architecture
Amazon Redshift is a massively parallel processing (MPP), columnar, shared-nothing data warehouse:
- Leader node -- Receives client connections, parses SQL, generates optimized query plans, coordinates compute nodes, and aggregates final results. Does not store user data.
- Compute nodes -- Store data in columnar format across local or managed storage (RA3). Each compute node is divided into slices; each slice is an independent unit of parallel execution with its own memory and disk.
- Slices -- The fundamental unit of parallelism. An RA3.xlplus node has 2 slices; RA3.4xlarge has 4; RA3.16xlarge has 16. Data distribution maps rows to slices.
- Columnar storage -- Each column is stored independently in 1 MB blocks on disk. Only columns referenced in the query are read.
- Zone maps -- Automatic in-memory min/max metadata per 1 MB block. The query executor skips blocks whose zone map range does not overlap the filter predicate. This is why sort keys are critical.
- Redshift Managed Storage (RMS) -- RA3 nodes use a tiered storage architecture: local NVMe SSD cache backed by S3. Hot data stays local; cold data is transparently fetched from S3. Storage scales independently of compute.
What ships with it
4 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.
- 8d ago First seen · 414 lines · 108 tokens per session scan A 5ae37c155c37
database-redshift is a skill published in the GitHub repository Kilo-Org/kilo-marketplace (175 stars, last pushed 22d ago), licensed Apache-2.0. It adds 108 tokens to every session and 4,345 once invoked, about $0.0005 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 2026-09-03.
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