Borrowing it
Nothing to install: this file belongs to Daegyu519/portfolio-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Daegyu519/portfolio-agent/main/.claude/commands/daily.mdgit clone --depth 1 https://github.com/Daegyu519/portfolio-agentWrote 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/daegyu519/portfolio-agent/daily)<a href="https://agentmods.dev/commands/daegyu519/portfolio-agent/daily"><img src="https://agentmods.dev/badge/commands/daegyu519/portfolio-agent/daily/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/daegyu519/portfolio-agent/daily"><img src="https://agentmods.dev/badge/commands/daegyu519/portfolio-agent/daily.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 | $0.00023 | $0.00245 |
| Opus 5 | $0.00012 | $0.00122 |
| Sonnet 5 | $0.00005 | $0.00049 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
daily 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 8d 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
python -m src.cli.brief daily 를 Bash 로 실행하라 (인자가 있으면 그대로 전달 — 예: --mock).
출력에서 다음만 사용자에게 전하라. 재해석·재계산 금지 — 수치는 전부 코드 산출이다:
- 요약 라인 (점검 논지 수·전이·임계 플래그)
- 전이 목록 (있을 때만)
- Daily 페이지 저장 결과 (지식 export 라인)
전이나 임계 플래그가 있으면 "심층 판단이 필요하면 /review" 한 줄만 덧붙여라. 그 외 분석·의견·요약문을 새로 만들지 마라.
참고: 매일 자동 발행은 이 커맨드가 아니라 watch(WATCH_DAILY_AT)/cron 이 LLM 토큰 0으로 수행한다. 이 커맨드는 세션 안에서 지금 즉시 한 번 돌리고 싶을 때만 쓰는 수동 트리거다.
$ARGUMENTS
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.
- 8d ago First seen · 19 lines · 23 tokens per session scan A d5d23e4ab47f
daily is a command published in the GitHub repository Daegyu519/portfolio-agent (0 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 245 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
portfolio
View TastyTrade portfolio summary (positions and balances).
security-audit
Full security pass - verify, validate and harden this repo against its real threat model.
sages
Summon the Market Sages council to analyze a stock (e.g. /sages AAPL, /sages NVDA --value).
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.