rehashing-datavault4dbt-entities

rehashing-datavault4dbt-entities is a skill for Claude Code from ScalefreeCOM/datavault4dbt-agent-skills. It costs 90 tokens per session (1,256 once invoked), scanned A, original, Apache-2.0.

A data-migration workflow for recalculating hash keys and hash differences in an existing Raw Data Vault. A Raw Data Vault is a warehouse layer that stores historical source data, while hashes are generated values used to identify records and changes.

In plain words
What is it for?
Use it during hash-logic changes or the datavault4dbt v1-to-v2 upgrade to rehash existing entities, test one entity first, preserve old values during migration, and verify referential integrity.
Why use it?
Changing the hash algorithm, data type, trimming, case rules, or package version can make old and new hashes disagree, breaking links between records. Rehashing updates existing data when the complete source history cannot be loaded again.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it during hash-logic changes or the datavault4dbt v1-to-v2 upgrade to rehash existing entities, test one entity first, preserve old values during migration, and verify referential integrity.

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Install with agentmods
npx agentmods add skills/scalefreecom/datavault4dbt-agent-skills/rehashing-datavault4dbt-entities
Install

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.

Any agent
npx skills add ScalefreeCOM/datavault4dbt-agent-skills --skill rehashing-datavault4dbt-entities
Clone the repo
git clone --depth 1 https://github.com/ScalefreeCOM/datavault4dbt-agent-skills

Made for: Claude Code.

Wrote this? Show the measurements

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README.md
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<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>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,256 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 12d ago against content hash 1603840ed5e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

skills/datavault4dbt/skills/rehashing-datavault4dbt-entities/SKILL.md · 133 lines

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 (MD5SHA2), 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:

  1. Full refresh the RDV (only if the full source history is still available to reload), or
  2. 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 longer UPPER-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)

  1. Start small — rehash one test entity first and verify the configuration and logic.
  2. Overwrite, don't drop — set overwrite_hash_values: true and keep drop_old_values: false. The macros rename the old columns with a _deprecated suffix instead of deleting them.
  3. Validate — compare the new hash columns against the _deprecated columns.
  4. 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

Read the full file on GitHub · 133 lines

Changes

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.

  1. 12d ago First seen · 133 lines · 90 tokens per session scan A 1603840ed5e1

Subscribe to this mod's changes

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.

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