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 agentmods add skills/altimateai/altimate-code/training-statusnpx skills add AltimateAI/altimate-code --skill training-statusgit clone --depth 1 https://github.com/AltimateAI/altimate-codeWhat 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 | $0.00019 | $0.00323 |
| Opus 5 | $0.00010 | $0.00161 |
| Sonnet 5 | $0.00004 | $0.00065 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
training-status 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 3d 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.
What it actually says
Training Status
Purpose
Display a comprehensive overview of everything your AI teammate has been trained on.
Workflow
-
Fetch all training: Use the
training_listtool with no filters to get all training entries. -
Present the dashboard: Format the output as a clean status report:
Training Status
Patterns: X (staging-model, incremental-config, ...)
Rules: X (no-float, no-select-star, ...)
Glossary: X (arr, mrr, churn-date, ...)
Standards: X (sql-style-guide, review-checklist, ...)
Recent Training:
- 2 days ago: Learned rule "no-float" (from user correction)
- 5 days ago: Learned pattern "staging-model" (from stg_orders.sql)
- 1 week ago: Loaded standard "sql-style-guide" (from docs/sql-style.md)
Most Applied:
- "staging-model" pattern — applied 12 times
- "no-float" rule — applied 8 times
- Offer actions: After showing status, suggest:
/teachto learn new patterns/trainto load standards from documentstraining_removeto remove outdated entriestraining_listwith filters for detailed views
Usage
/training-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.
- 3d ago First seen · 46 lines · 19 tokens per session scan A 103b54836200
training-status is a skill published in the GitHub repository AltimateAI/altimate-code (803 stars, last pushed 3d ago), licensed MIT. It adds 19 tokens to every session and 323 once invoked, about $0.0001 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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