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 iblai/enterprise-agents --skill snowflakegit clone --depth 1 https://github.com/iblai/enterprise-agentsWrote 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/iblai/enterprise-agents/snowflake)<a href="https://agentmods.dev/skills/iblai/enterprise-agents/snowflake"><img src="https://agentmods.dev/badge/skills/iblai/enterprise-agents/snowflake.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 5.1 | $0.00034 | $0.00623 |
| Opus 5 | $0.00017 | $0.00311 |
| Sonnet 5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
snowflake 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Snowflake
What it is
Snowflake is the leading cloud data warehouse platform, used by enterprise data and analytics teams as the central repository for structured business data. In this segment the data analysis agent uses Snowflake to run ad-hoc SQL queries, retrieve metric snapshots, and explore data model lineage. All access is read-only, routed through a dedicated reporting warehouse to avoid impacting production workloads.
When to use this skill
- Running a SQL query to answer a business question about revenue, headcount, or operational KPIs
- Exploring available databases, schemas, and tables before constructing a query
- Fetching query results to populate a report or dashboard narrative
- Checking table row counts and last-updated timestamps to assess data freshness
- Validating a metric definition against the underlying table structure
Credentials
This skill authenticates using variables from ~/.openclaw/.env (template: .env.example at the config root). Required variables:
SNOWFLAKE_ACCOUNT- account identifier (e.g.myorg-myaccount)SNOWFLAKE_USER- service account usernameSNOWFLAKE_PASSWORD- service account password (or use key-pair; see Notes)SNOWFLAKE_WAREHOUSE- virtual warehouse to use for query executionSNOWFLAKE_DATABASE- default database contextSNOWFLAKE_SCHEMA- default schema contextSNOWFLAKE_ROLE- role to assume (should be a read-only reporting role)
Key operations
POST /api/v2/statements- execute a SQL statement via the Snowflake SQL REST APIGET /api/v2/statements/{statementHandle}- poll for async query resultsSHOW DATABASES- list available databasesSHOW SCHEMAS IN DATABASE {db}- list schemasSHOW TABLES IN SCHEMA {db}.{schema}- list tables with metadata
Notes
- Always use a dedicated read-only role; never grant ACCOUNTADMIN or SYSADMIN to the service account.
- Set
QUERY_TAGon each session to identify agent-generated queries in the query history for auditing. - Credit consumption depends on warehouse size; use XS or S warehouse for reporting queries.
- Key-pair authentication is preferred over password for production; store private key path separately.
- Results larger than 10 MB are returned via pre-signed S3/GCS/Azure URLs in the REST API response.
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 · 42 lines · 34 tokens per session scan A 3cd29cdb8720
snowflake is a skill published in the GitHub repository iblai/enterprise-agents (11 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 623 once invoked, about $0.0002 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.
Other skills, from other repositories
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.
sql-optimization-patterns
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.
cqrs-implementation
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
projection-patterns
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
software-database-design
Designs database schemas, migrations, and data models for PostgreSQL, MySQL, MongoDB, and Redis. Use when planning tables, relationships, indexes, or ORM-backed schema changes.