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 AltimateAI/altimate-claude-plugin --skill altimate-codegit clone --depth 1 https://github.com/AltimateAI/altimate-claude-pluginWrote 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/altimateai/altimate-claude-plugin/altimate-code)<a href="https://agentmods.dev/skills/altimateai/altimate-claude-plugin/altimate-code"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-claude-plugin/altimate-code/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/altimateai/altimate-claude-plugin/altimate-code"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-claude-plugin/altimate-code.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 | $0.00182 | $0.02012 |
| Opus 5.5 | $0.00073 | $0.00805 |
| Sonnet 5.5 | $0.00036 | $0.00402 |
| Haiku 4.5 | $0.00018 | $0.00201 |
Grade C, and why
altimate-code scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
`refactor `whoami` and $(rm -rf ~)` would otherwise fire `whoami` and How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
altimate-code
altimate-code is a CLI AI agent with 100+ purpose-built data engineering tools. This skill exists for one purpose: delegate the user's task to altimate-code and pass the result back. Native tools (Bash, Edit, Write, Read) are NOT a fallback path inside this skill — if altimate-code cannot complete the task, surface the failure to the user and STOP.
You MUST follow this workflow
- Verify altimate-code is on PATH with
command -v altimate-code. If it returns nothing, jump to "Not installed" below and stop. - Run altimate-code with the user's task using the invocation below. Pass the user's request through verbatim — do not paraphrase or split it.
- Read the output file and present it to the user as-is.
Do not attempt the work with Edit/Write/Bash yourself, even if it looks simple. The whole point of this skill is to route data-engineering work to the agent that's built for it. If you find yourself reaching for Edit or Write while this skill is active, stop and re-read this paragraph.
Invocation — pick the right agent for the task
altimate-code has multiple agent personas. The default (builder) does a full project discovery sweep on every call — fine for warehouse-state work but ~10–20× more expensive than necessary on simple file edits. Pick the agent based on task shape before invoking.
Step 1 — classify the task
| Shape | Examples | Use |
|---|---|---|
| Any dbt / SQL task (rename, refactor, create model, debug, structural reorg, multi-step setup) | the vast majority of customer requests | fast-edit — try this first |
| Multi-table aggregation correctness | new model joining 3+ tables with count(*) / sum() over (...) / "first X, last X" logic that must be exactly right |
analyst if fast-edit fails the user's verification |
| Warehouse-state work | column-level lineage, downstream-impact, cross-DB migration / parity, query cost attribution against a real warehouse, schema diff between environments, PII detection, FinOps reporting | builder (default — has warehouse tools enabled) |
| Vague debug ("X is broken", "make it work", "fix this") | unspecified failure mode | Don't delegate yet. Ask the user for the specific error message or symptom before invoking any agent — empirically all three agents fail vague debug prompts at ~700K tokens each. |
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 · 120 lines · 182 tokens per session scan C 0ec697b5215c
altimate-code is a skill published in the GitHub repository AltimateAI/altimate-claude-plugin (4 stars, last pushed today), licensed MIT. It adds 182 tokens to every session and 2,012 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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