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/mworldorg/markdown-memory/mm-setupnpx skills add mworldorg/markdown-memory --skill mm-setupgit clone --depth 1 https://github.com/mworldorg/markdown-memoryWhat 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 | $0.00152 | $0.02107 |
| Opus 5 | $0.00076 | $0.01053 |
| Sonnet 5 | $0.00030 | $0.00421 |
| Haiku 4.5 | $0.00015 | $0.00211 |
Grade A, and why
mm-setup 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 2d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mm-setup — Персонализация mm-системы под пользователя
Делает систему «своей»: имя, домен, стек, пути — без правки committed-файлов (репо общий, расшарен на GitHub). Личное идёт в gitignored оверлей и в генерируемую персональную копию claude.ai-скилла.
Контракт безопасности (соблюдай дословно)
Skill ПИШЕТ только в:
<repo>/config/mm-config.local.json— создаёт или мёрджит (gitignored, личный оверлей)<repo>/claude-ai-skills/_generated/mm-web-bridge/SKILL.md— персональная копия для загрузки в claude.ai (gitignored)
Skill НИКОГДА не трогает:
config/mm-config.json(committed — общие дефолты louise; их не перезаписываем)claude-ai-skills/mm-web-bridge/SKILL.md(committed шаблон — читаем как источник, не правим)- любые
skills/*/SKILL.md,~/.claude/CLAUDE.md(для глобального — только предложим сниппет) - git-операции
Конфиг
Загрузи mm-config.json по алгоритму из <repo>/docs/CONFIG-LOADING.md (нужен _repo_root). Если уже есть mm-config.local.json — прочитай его как текущие значения (режим повторной настройки).
Шаг 1. Интервью
Задай одним сообщением (не по одному вопросу), с разумными дефолтами в скобках:
Настрою mm-систему под тебя. Ответь (можно коротко):
1. Имя — как тебя называть? <текущее из config, если есть>
2. Чем занимаешься / домен? (например: «Telegram-боты», «веб на React», «data-инженерия»)
3. Основной стек? (язык · фреймворк · БД · деплой — например «Python · aiogram 3.x · SQLite · Railway»)
4. Язык общения по умолчанию? (ru / en) <текущий default_language>
5. Путь к Obsidian vault? <текущий obsidian_vault, или предложи C:\Users\<user>\Documents\Obsidian Vault>
Дополнительно (не спрашивай, выведи сам):
<user>для дефолтных путей возьми из$env:USERPROFILE/~.- Если на п.5 дают только vault — остальные obsidian-пути (
Claude/,Bridge/,Sessions/,Projects/,INDEX.md) выведи относительно него по той же структуре, что в committedmm-config.json. - Если пользователь говорит «как у тебя в дефолте / пропусти» — оставь committed-значение (не дублируй его в local без нужды).
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.
- 2d ago First seen · 137 lines · 152 tokens per session scan A a560b8d0851f
mm-setup is a skill published in the GitHub repository mworldorg/markdown-memory (25 stars, last pushed 15d ago), licensed MIT. It adds 152 tokens to every session and 2,107 once invoked, about $0.0008 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.
Other skills, from other repositories
performance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now…
test-driven-development
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
observability-and-instrumentation
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
documentation-and-adrs
Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.