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 ScalefreeCOM/datavault4dbt-agent-skills --skill rehashing-datavault4dbt-entitiesgit clone --depth 1 https://github.com/ScalefreeCOM/datavault4dbt-agent-skillsWrote 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/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities)<a href="https://agentmods.dev/skills/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities"><img src="https://agentmods.dev/badge/skills/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities/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/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities"><img src="https://agentmods.dev/badge/skills/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities.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 | $0.00090 | $0.01256 |
| Opus 5 | $0.00045 | $0.00628 |
| Sonnet 5 | $0.00018 | $0.00251 |
| Haiku 4.5 | $0.00009 | $0.00126 |
Grade A, and why
rehashing-datavault4dbt-entities 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 12d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rehashing datavault4dbt entities
When you change anything that affects hash output — the algorithm (MD5→SHA2), hash_datatype,
hashdiff_use_trim, or case-sensitivity vars — every hashkey and hashdiff in the Raw Data Vault must
change too, or referential integrity breaks. You have two options:
- Full refresh the RDV (only if the full source history is still available to reload), or
- Rehash existing entities in place with the package's rehashing macros (when history is not reloadable).
This skill is about option 2.
v1 → v2.0.0 upgrade. v2.0.0 unifies/corrects hash standardization: with default settings, hashkeys are now
UPPER-normalized and hashdiffs are no longerUPPER-normalized, plus adapter-specific changes (Oracle/Redshift concat-string alignment, BigQuery MD5 fix, Fabric/Exasol standardization). Hash values differ from v1, so crossing this boundary on an existing vault requires a full refresh or a rehash.
The safe workflow (always)
- Start small — rehash one test entity first and verify the configuration and logic.
- Overwrite, don't drop — set
overwrite_hash_values: trueand keepdrop_old_values: false. The macros rename the old columns with a_deprecatedsuffix instead of deleting them. - Validate — compare the new hash columns against the
_deprecatedcolumns. - Clean up — only after validation, drop the deprecated columns. The dbt log prints the dict of
columns to drop; use it to build a cleanup model or call
datavault4dbt.custom_alter_relation_add_remove_columns.
Single-entity rehash (surgical)
Run a one-off operation against a single hub/link/satellite:
dbt run-operation rehash_single_hub --args '{
hub: customer_h,
hashkey: HK_CUSTOMER_H,
business_keys: C_CUSTKEY,
overwrite_hash_values: true
}'
Bulk rehash by entity type (YAML-driven)
Create a dedicated model that calls the bulk macro with YAML metadata:
-- models/rehash/rehash_hubs.sql
{{ config(materialized='view') }}
{% set hub_yaml %}
config:
overwrite_hash_values: true
hubs:
- name: customer_h
hashkey: hk_customer_h
business_keys: [c_custkey]
- name: order_h
hashkey: hk_order_h
business_keys: [order_id]
{% endset %}
{{ datavault4dbt.rehash_hubs(hub_yaml=hub_yaml, drop_old_values=false) }}
SELECT 'success' as status
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.
- 12d ago First seen · 133 lines · 90 tokens per session scan A 1603840ed5e1
rehashing-datavault4dbt-entities is a skill published in the GitHub repository ScalefreeCOM/datavault4dbt-agent-skills (22 stars, last pushed 15d ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,256 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 2026-08-30.
Other skills, from other repositories
dynamodb
AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.
rds
AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.
exasol
Top-level router for Exasol work. Use for any Exasol database, exapump, SQL, BucketFS, extension, integration, UDF, Script Language Container, or Exasol Personal setup task, then route to the narrowest specialized Exasol skill.
exasol-database
Exasol database interaction via the exapump CLI and Exasol SQL. Covers SQL queries and DML/DDL such as SELECT, INSERT, UPDATE, DELETE, MERGE, CREATE TABLE, ALTER TABLE, and DROP TABLE, CREATE CONNECTION connection objects without import or export intent, schema inspection, table design, exapump sql and exapump…
exasol-udfs
Exasol User Defined Functions (UDFs) and Script Language Containers (SLCs). Covers CREATE SCRIPT, SCALAR and SET functions, variadic scripts with EMITS(...) and defaultoutputcolumns, the ExaIterator and ExaMetadata APIs, Python, Java, Lua, and R scripts, Lua execute scripts and pquery, BucketFS file access…
exasol-bucketfs
Exasol BucketFS file system management via the exapump bucketfs CLI. Covers listing, uploading, downloading, and deleting files and directories in BucketFS, the bfsdefault service and other bucket services, bucket structure, bfs profile settings, the /buckets/ / / UDF path, and staging JARs, models, and Script…