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 agentmods add skills/bytesagain/ai-skills/alphanpx skills add bytesagain/ai-skills --skill alphagit clone --depth 1 https://github.com/bytesagain/ai-skillsWhat 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 | $0.00015 | $0.00345 |
| Opus 5 | $0.00008 | $0.00172 |
| Sonnet 5 | $0.00003 | $0.00069 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
alpha 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 2d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 104 lines · 15 tokens per session scan A 4f6b2ab12444
alpha is a skill published in the GitHub repository bytesagain/ai-skills (12 stars, last pushed 4mo ago), with no licence file. It adds 15 tokens to every session and 345 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 2026-08-30.
Other skills, from other repositories
transfer-bonuses
Active credit card transfer bonuses from Amex, Chase, Capital One, Citi, Bilt, and Rove. Weekly-refreshed data with confidence markers. Use when pricing an award booking that involves a points transfer or deciding whether to wait for a better bonus.
points-valuations
Cents-per-point (cpp) valuations across major loyalty programs from four publications. Floor/ceiling rules for deciding if a redemption is good or exceptional.
award-sweet-spots
Catalog of high-value award redemptions where points dramatically outvalue cash. Tiered by legendary/excellent/good with current rates, devaluation history, and booking caveats. Includes Oceania and South Pacific plays (Australia, New Zealand, Tahiti, Fiji) and transatlantic business-class sweet spots.
quant-experiment-runtime
Quant research experiment executor: discover an offline source database under the workdir's code-repo, build a panel, run a Research Artifact's entry point to compute research-object values, and evaluate IC/ICIR/RANKIC/coverage metrics. Runtime = Experiment Executor; it runs a Research Artifact via a Python-native…
fin-ref-paper
从LITREVIEW.md和IDEAREPORT.md中提取参考文献，自动生成符合JF/JFE/RFS/GB-T-7714格式的references.bib，并管理引用一致性。.
dcf-model
Build discounted cash flow valuation workbooks in Excel.