Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add cyrus-cai/claude-cobrain/plugin install claude-cobrainWrote 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/cyrus-cai/claude-cobrain/logs)<a href="https://agentmods.dev/skills/cyrus-cai/claude-cobrain/logs"><img src="https://agentmods.dev/badge/skills/cyrus-cai/claude-cobrain/logs/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/cyrus-cai/claude-cobrain/logs"><img src="https://agentmods.dev/badge/skills/cyrus-cai/claude-cobrain/logs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00008 | $0.00189 |
| Opus 5 | $0.00004 | $0.00095 |
| Sonnet 5 | $0.00002 | $0.00038 |
| Haiku 4.5 | $0.00001 | $0.00019 |
Grade A, and why
logs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
logs
Use direct python3 logs via controller script.
if [[ -n "${CLAUDE_PLUGIN_ROOT:-}" && -f "${CLAUDE_PLUGIN_ROOT}/scripts/control.sh" ]]; then
CONTROL_SCRIPT="${CLAUDE_PLUGIN_ROOT}/scripts/control.sh"
elif [[ -f "./plugin/scripts/control.sh" ]]; then
CONTROL_SCRIPT="./plugin/scripts/control.sh"
else
CONTROL_SCRIPT="$(ls -dt "$HOME"/.claude/plugins/cache/*/claude-cobrain/*/scripts/control.sh 2>/dev/null | head -1)"
fi
[[ -n "${CONTROL_SCRIPT:-}" && -f "$CONTROL_SCRIPT" ]] || { echo "control.sh not found. Run: /claude-cobrain:cobrain install"; exit 1; }
bash "$CONTROL_SCRIPT" logs
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.
- 10d ago First seen · 22 lines · 8 tokens per session scan A e2c9f32a7b2d
logs is a skill published in the GitHub repository cyrus-cai/claude-cobrain (5 stars, last pushed 6mo ago), licensed MIT. It adds 8 tokens to every session and 189 once invoked, about $0.0000 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.
Other skills, from other repositories
spark-engineer
Use when writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big data workloads. Invoke to write DataFrame transformations, optimize Spark SQL queries, implement RDD pipelines, tune shuffle operations, configure…
debugging-wizard
Parses error messages, traces execution flow through stack traces, correlates log entries to identify failure points, and applies systematic hypothesis-driven methodology to isolate and resolve bugs. Use when investigating errors, analyzing stack traces, finding root causes of unexpected behavior, troubleshooting…
Reverse Engineering & Binary Analysis
Binary analysis, assembly interpretation, disassembly, decompilation, firmware RE, and protocol reverse engineering.
perf-profiler
A performance investigation guide that uses repeatable measurements and profiling evidence to find where software spends time or resources. Profiling records runtime activity such as CPU use, memory use, database work, or network delays.
log-analyzer
A log-analysis helper that reads application and system logs to find unusual patterns and likely causes. Logs are records of events such as errors, requests, warnings, and service activity.
lcx-report-bug
Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing.