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 TserenTserenov/FMT-exocortex-template --skill fpfgit clone --depth 1 https://github.com/TserenTserenov/FMT-exocortex-templateWrote 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/tserentserenov/fmt-exocortex-template/fpf)<a href="https://agentmods.dev/skills/tserentserenov/fmt-exocortex-template/fpf"><img src="https://agentmods.dev/badge/skills/tserentserenov/fmt-exocortex-template/fpf/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/tserentserenov/fmt-exocortex-template/fpf"><img src="https://agentmods.dev/badge/skills/tserentserenov/fmt-exocortex-template/fpf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00042 | $0.01229 |
| Opus 5 | $0.00021 | $0.00615 |
| Sonnet 5 | $0.00008 | $0.00246 |
| Haiku 4.5 | $0.00004 | $0.00123 |
Grade A, and why
fpf 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 4d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Загрузка принципов
Запрос: $ARGUMENTS
When to use
Загрузка применимых принципов для задачи из иерархии Pack → SPF → FPF. Используй когда нужно найти релевантные принципы перед принятием решения.
Fallback Chain
Pack (предметное) → SPF (корректность) → FPF (первые принципы)
Режимы (определи по контексту запроса)
| Режим | Триггер | Что делать |
|---|---|---|
| lookup | Запрос содержит код паттерна (A.7, B.5, F.18) или конкретный термин | Grep по FPF → точная секция. Объясни в engineering-языке (см. memory/fpf-reference.md § Трансляция) |
| review | «Проверь», «сверь с FPF», артефакт для проверки | Загрузи артефакт + релевантные принципы → сверка пункт за пунктом → findings |
| design | «Спроектируй», «как сделать по FPF», задача проектирования | Подбери применимые паттерны (A.1 границы, A.6 состав, A.7 различения, B.5 ADI) → конкретные рекомендации |
| characterize | «Сравни», «оцени варианты», «как выбрать» | A.17-A.19 (Lawful Comparison): критерии → индикаторы → оценка вариантов по одинаковой шкале |
| teach | «объясни FPF», «что такое FPF», «с нуля», «введение» | Дай обзор FPF: что это, зачем, ключевые блоки (различения, паттерны, первые принципы) → объясни в engineering-языке без жаргона |
| diagnose | «какие принципы нарушаю», «что не так», «найди проблему», «проверь мою работу» | Получи описание работы/решения → найди расхождения с принципами FPF/Pack → назови конкретные нарушения с указанием принципа и где именно |
| prioritize | «наиболее важны», «для роли», «в роли», «для меня как» | Определи роль из аргумента → найди принципы FPF/Pack, релевантные этой роли → ранжируй по применимости → объясни почему каждый важен именно для этой роли |
БЛОКИРУЮЩЕЕ — No-Jargon: Каждый FPF-термин в output → engineering-эквивалент в скобках или вместо. Без исключений.
- Известные:
memory/fpf-reference.md§ Трансляция (Holon, F-G-R, Alpha, Mereology, Affordance, ADI...) - Неизвестные (TransformerRole, senseFamily, Γ_*, ReferencePlane и т.п.): перевести по контексту, добавить
(FPF: <оригинал>). Не оставлять FPF-термин без перевода. - Тест перед выводом: пробежать output — есть ли термин, непонятный инженеру без FPF? Если да — перевести.
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.
- 4d ago Changed · +1 lines 7910297fcbc1
- 9d ago First seen · 84 lines · 42 tokens per session scan A 68e079768912
fpf is a skill published in the GitHub repository TserenTserenov/FMT-exocortex-template (50 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 1,229 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 2026-08-30.
Other skills, from other repositories
team-management-debugging
Systematic debugging — a four-phase root-cause methodology, boundary instrumentation for multi-component systems, the 3-fix escalation rule, and a verification gate to run before claiming anything is fixed. Use on any test failure, production bug, build failure, performance regression, or integration glitch, and…
team-management-receiving-feedback
How to receive code review as technical evaluation rather than social performance — verify claims against the codebase before implementing, push back with evidence, and drop the performative agreement. Use when responding to a human reviewer, a PR comment, or another AI reviewer, and when deciding whether a suggestion…
team-management-tdd-discipline
Test-driven development discipline — when TDD applies, when forcing it is wrong, and the RED-GREEN-REFACTOR loop with an explicit "watch it fail" step. Use when writing or reviewing tests, fixing a bug, changing behaviour, or deciding whether a change needs a test at all. Triggers on bug fixes, new validation or…
data-profiling
Use BEFORE dispatching any subagent that needs to understand the dataset. Generates a high-density, PII-free data profile in Markdown so subagents receive structured context instead of raw data.
leakage-guard
Use whenever building features for time-series or any temporal dataset. Enforces strict temporal integrity: no future data in features, no post-event information, correct CV strategy.
verification-before-delivery
Use when any analysis, model, or report is claimed to be complete. Runs mandatory artifact integrity, statistical evidence, and reproducibility checks before any delivery.