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/infohata/mind-vault/pythonnpx skills add infohata/mind-vault --skill pythongit clone --depth 1 https://github.com/infohata/mind-vaultWhat 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 | $0.00037 | $0.01175 |
| Opus 5 | $0.00018 | $0.00588 |
| Sonnet 5 | $0.00007 | $0.00235 |
| Haiku 4.5 | $0.00004 | $0.00118 |
Grade A, and why
python 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 yesterday.
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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
python
The vault's base Python-language layer — the deliberate home for engineering
patterns that are true of any Python project, framework or not. It sits
beneath the framework-stack skills (django, django-frontend, and future
fastapi/flask/etc.): those skills own framework concepts (ORM, request
lifecycle, background jobs, templating); this skill owns language-general
mechanics that would otherwise misfile into whichever framework skill happened
to need them first. New Python-general patterns land here — not under a
framework skill by gravity. Framework skills point down into this layer's
references rather than copying the recipes.
When to use
TRIGGER when: working a Python task whose mechanics are language-general — restructuring a large flat module into a package, parsing per-deployment config into immutable in-memory lookups, and similar stdlib-level engineering — and the recipe doesn't depend on a specific framework's runtime.
SKIP when: the task is framework-specific — defer to the repo's active framework-stack skill (django / django-frontend today; laravel and others once IDEA-014's stack detection lands). python is the broadest false-positive surface in the vault (almost everything touches a .py file); it must NOT fire on, or double-load alongside, a framework task. When framework context is present, the framework skill leads and reaches down into these references as needed — python does not also activate.
Pattern
1. Splitting a flat module into a package
Fires when a single large module (views.py, models.py, a multi-kLOC
domain module) needs to become a package with per-domain submodules + a
re-exporting __init__.py, and you want the move reviewable as a move (zero
transcription risk), not a rewrite.
The shape: drive the extraction with Python's ast so each symbol is sliced
byte-exact from the original; bucket by name-prefix into submodules; assert
lossless line-coverage before writing; blank-line-only autopep8 + pyflakes
import-trim so the diff stays a clean move. It also owns the
RULE_rename-before-drop
forced-atomic-member wrinkle (a module and a package can't share a dotted
name). Full recipe, AST-omission edge cases, and the mixed-bridge sequencing are
in references/MODULE_SPLIT_AST_EXTRACTION.md.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 62 lines · 37 tokens per session scan A 0cb03654b998
python is a skill published in the GitHub repository infohata/mind-vault (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,175 once invoked, about $0.0002 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 2026-08-31.
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