COG is an AI-assisted second brain that stores knowledge in Markdown files and uses agents, skills, and version control to evolve it over time. It helps people manage knowledge and contacts while supporting several coding-agent tools; the catalogue entries are COG’s skills, agents, instructions, rules, and plugin surfaces.
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 huytieu/COG-second-brain --skill loop-engineeringgit clone --depth 1 https://github.com/huytieu/COG-second-brainWrote 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/huytieu/cog-second-brain/loop-engineering)<a href="https://agentmods.dev/skills/huytieu/cog-second-brain/loop-engineering"><img src="https://agentmods.dev/badge/skills/huytieu/cog-second-brain/loop-engineering/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/huytieu/cog-second-brain/loop-engineering"><img src="https://agentmods.dev/badge/skills/huytieu/cog-second-brain/loop-engineering.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 Agent Snooping · line 6 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00063 | $0.00150 |
| Opus 5.5 | $0.00025 | $0.00060 |
| Sonnet 5.5 | $0.00013 | $0.00030 |
| Haiku 4.5 | $0.00006 | $0.00015 |
Grade A, and why
loop-engineering 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.
What it actually says
Read .claude/skills/loop-engineering/SKILL.md and execute it exactly as written — that file is the authoritative
playbook. Then follow .agents/rules/cog.md.
Antigravity substitution: where the playbook delegates to a .claude/agents/<name>
worker, invoke .agents/agents/<name>.md via invoke_subagent instead.
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 First seen · 11 lines · 63 tokens per session scan A 0ee060d9b289
loop-engineering is a skill published in the GitHub repository huytieu/COG-second-brain (1,315 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 150 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.
Other skills, from other repositories
debugging
Playwright test debugging conventions for the scaffold — reading failure messages, classifying failure modes (TimeoutError, ZodError, strict-mode violation, locator not found, network errors, schema drift), the playwright.config.ts capture defaults (trace on-first-retry, screenshot only-on-failure, video…
investigate
Forensic bug triage — rank suspects via lawbookinvestigate before draft --bug. Use with a stack trace or symptom when starting RCA.
test-failure-explorer
Import and query an existing Vitest 3.2 JSON report to explore test failures, file-level errors and original diagnostic evidence.
diagnose-backend-bug
Diagnose a bounded backend or multi-service failure from GitHub Issues, Jira, Aone, user-provided exports, logs, traces, responses, stack traces, or job records. Use when a service, API, RPC, worker, queue, CLI, or scheduled job bug needs correlation through the project's existing observability route before repair; do…
prismer-python-debugpy
Debug Python: pdb REPL + debugpy remote (DAP).
debug-live
Guides root-cause investigations with debugging capabilities by setting breakpoints, starting a debug session, stepping through execution, inspecting variables, and tracing symptoms back to their origin. Prefer it for runtime bugs, failing tests, exceptions, crashes, hangs, wrong/null values, and unexpected output…