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 w-reflectiongit 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/w-reflection)<a href="https://agentmods.dev/skills/tserentserenov/fmt-exocortex-template/w-reflection"><img src="https://agentmods.dev/badge/skills/tserentserenov/fmt-exocortex-template/w-reflection/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/w-reflection"><img src="https://agentmods.dev/badge/skills/tserentserenov/fmt-exocortex-template/w-reflection.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 | $0.00077 | $0.01012 |
| Opus 5.5 | $0.00031 | $0.00405 |
| Sonnet 5.5 | $0.00015 | $0.00202 |
| Haiku 4.5 | $0.00008 | $0.00101 |
Grade A, and why
w-reflection 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 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.
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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
W-Reflection — запись мировоззренческого индикатора
Назначение: populate
learning.w_reflectionsдля расчётаW.idxв SR-алгоритме (FORM.089 §5). Когда вызывать: после рефлексивной сессии (диалог с Диагностом R28, индивидуальный самоанализ, разбор мировоззренческой ошибки). Не для рутинной фиксации настроения — это калибровка. Влияние: W ≥ 4 обязательно для перехода Дисциплинированный → Проактивный (gate Д→П).
When to use
Записать W-рефлексию (мировоззренческий слот RCS) в learning.w_reflections. Используется Диагностом R28 (MIM.R.009) или вызывается пользователем после рефлексивной сессии. Влияет на gate Д→П (FORM.089 §5.2).
Аргументы
$1 = quality_score— 1..5 по рубрике:- 1 — поверхностная (констатация без причин)
- 2 — описательная (есть «что было», нет «почему»)
- 3 — анализирующая (причины, последствия)
- 4 — системная (видение себя как системы, agency)
- 5 — мета-системная (видение себя как роли в надсистеме)
$2 = depth_level(опционально, default 2) — 1..3:- 1 — поверхностная
- 2 — средняя (стандарт)
- 3 — глубокая (>30 мин разбора)
Algorithm
Шаг 1. Вызвать скрипт маршрутизации
bash "$IWE_SCRIPTS/route-task.sh" --skill w-reflection --args "$ARGUMENTS"
Скрипт читает IWE_OWNER_ORY_UUID из окружения (account_id) и пишет в learning.w_reflections через роль w_reflection_writer (миграция 112). При отсутствии writer-URL — fallback на DATABASE_URL_LEARNING_DIRECT.
Шаг 2. Проверить exit code
Exit codes и их значения — в разделе Выход ниже.
Шаг 3. Вернуть ответ пилоту
При exit 0 — вывести OK-строку из stdout. При ненулевом exit — вывести ошибку.
Выход
- exit 0 +
[w-reflection] OK: account=... quality=N depth=M— успех - exit 1 — невалидные аргументы
- exit 2 — отсутствует
IWE_OWNER_ORY_UUIDили DB URL - exit 3 — ошибка БД (constraint violation, network)
Пример
/w-reflection 3 # quality=3, depth=2 (default)
/w-reflection 4 3 # quality=4, глубокая
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 Changed · +1 lines 9f4128ce42f0
- 1mo ago First seen · 86 lines · 77 tokens per session scan A 63656d44602a
w-reflection is a skill published in the GitHub repository TserenTserenov/FMT-exocortex-template (63 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 1,012 once invoked, about $0.0003 per session on Opus 5.5. 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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