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.
git clone --depth 1 https://github.com/leefufufufufu-rgb/aibtiWrote 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/commands/leefufufufufu-rgb/aibti/aibti-today)<a href="https://agentmods.dev/commands/leefufufufufu-rgb/aibti/aibti-today"><img src="https://agentmods.dev/badge/commands/leefufufufufu-rgb/aibti/aibti-today/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/commands/leefufufufufu-rgb/aibti/aibti-today"><img src="https://agentmods.dev/badge/commands/leefufufufufu-rgb/aibti/aibti-today.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 | $0.00013 | $0.00248 |
| Opus 5 | $0.00006 | $0.00124 |
| Sonnet 5 | $0.00003 | $0.00050 |
| Haiku 4.5 | $0.00001 | $0.00025 |
Grade A, and why
aibti-today 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 12d 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
/aibti-today
生成今日 AIBTI 快照,了解今天你和 AI 的协作风格。
执行步骤
- 加载
aibtiSkill - 只扫描今天 (UTC+8) 的
~/.claude/projects/**/*.jsonl - 按 Skill 逻辑打标签
- 输出简化版报告(无需长篇幅诊断,只要:今日主人格 + 四维 + 3 条代表 prompt)
输出格式示例
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AIBTI · Today's Snapshot
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
今日人格: 🔮 AMLX 碎碎念诗人
对话数: 47 条
四维: A 62% · M 58% · L 71% · X 68%
代表提问:
· "..."
· "..."
· "..."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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.
- 12d ago First seen · 32 lines · 13 tokens per session scan A b031364309de
aibti-today is a command published in the GitHub repository leefufufufufu-rgb/aibti (3 stars, last pushed 4mo ago), licensed MIT. It adds 13 tokens to every session and 248 once invoked, about $0.0001 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 commands, from other repositories
yolo-validate
Run the YOLO change-validation suite — evaluate (4 layers), surface prioritized improvements, optionally apply fixes, then iterate to green. Maintainer tooling; explicit-invoke only.
implement-graphql-api
Command "implement-graphql-api" from qdhenry/Claude-Command-Suite, covering implement graphql api and instructions.
add-performance-monitoring
Setup application performance monitoring.
architecture-scenario-explorer
Explore architectural decisions through systematic scenario analysis with trade-off evaluation and future-proofing assessment.
parallel-feature-build
Orchestrated parallel implementation of complex features using multiple agents, with dependency-aware batching and synchronized progress tracking.
implement-caching-strategy
Command "implement-caching-strategy" from qdhenry/Claude-Command-Suite, covering implement caching strategy and instructions.