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 cruxible-ai/cruxible --skill prepare-datagit clone --depth 1 https://github.com/cruxible-ai/cruxibleWrote 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/cruxible-ai/cruxible/prepare-data)<a href="https://agentmods.dev/skills/cruxible-ai/cruxible/prepare-data"><img src="https://agentmods.dev/badge/skills/cruxible-ai/cruxible/prepare-data/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/cruxible-ai/cruxible/prepare-data"><img src="https://agentmods.dev/badge/skills/cruxible-ai/cruxible/prepare-data.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00037 | $0.00969 |
| Opus 5.5 | $0.00015 | $0.00388 |
| Sonnet 5.5 | $0.00007 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
prepare-data 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 1mo 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prepare Data
Use this skill before create-state, and before overlay-and-fit whenever local source files need to be loaded into an overlay.
Cruxible validates, loads, and evaluates. File cleaning and transforms are external.
This skill is about source-data preparation only:
- profiling files
- validating keys and joins
- checking grain and cardinality
- identifying cleaning and transform work
- producing cleaned files or a preparation plan
It is not for cross-dataset matching or governed relationship design. Those happen later in the state-building flow.
Use your own tools freely here: Python, Polars, SQL, spreadsheets, or shell tooling. The goal is to hand the later skills source files that are understood, defensible, and ready.
Workflow
Phase 1: Inventory the files
For each file, identify:
- what the file appears to represent
- whether it looks like an entity source, deterministic relationship source, reference file, or unknown source
- what its likely row grain is
- what other files it seems to join to
Do not assume the target state shape is already known. This skill is part of discovering it.
Phase 2: Profile each file
For every source file, inspect:
- row count
- columns
- dtypes
- null counts
- sample rows
- obvious schema inconsistencies across files of the same kind
Do not stop at one-line summaries. The point is to understand what later modeling and loading work would actually consume.
Phase 3: Validate entity keys and relationship joins
For likely entity files, check:
- duplicate primary keys
- null or empty IDs
- whitespace, prefix garbage, or sentinel values in IDs
- whether the file grain is really one row per entity
For likely deterministic relationship files, check:
- source and target key columns exist
- foreign keys actually resolve against the referenced entity files
- duplicate
(from, to, relationship_type)rows - whether the file grain is really one row per relationship
Across files, check:
- shared join columns exist where expected
- values actually overlap
- types are compatible
- normalization work is needed before joins can succeed
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.
- 1mo ago First seen · 150 lines · 37 tokens per session scan A 1a8146785495
prepare-data is a skill published in the GitHub repository cruxible-ai/cruxible (17 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 969 once invoked, about $0.0001 per session on Opus 5.5. 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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