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 modelstudioai/cli --skill bailian-finetunegit clone --depth 1 https://github.com/modelstudioai/cliWrote 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/modelstudioai/cli/bailian-finetune)<a href="https://agentmods.dev/skills/modelstudioai/cli/bailian-finetune"><img src="https://agentmods.dev/badge/skills/modelstudioai/cli/bailian-finetune/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/modelstudioai/cli/bailian-finetune"><img src="https://agentmods.dev/badge/skills/modelstudioai/cli/bailian-finetune.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 Prompt Injection · line 40 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00250 | $0.02150 |
| Opus 5.5 | $0.00100 | $0.00860 |
| Sonnet 5.5 | $0.00050 | $0.00430 |
| Haiku 4.5 | $0.00025 | $0.00215 |
Grade A, and why
bailian-finetune 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bailian fine-tuning pipeline (bl dataset / bl finetune / bl deploy)
CRITICAL — Before executing, MUST read the shared protocol in ../bailian-protocol/SKILL.md: Version & updates (pre-flight checklist), Call attribution (every Agent bl command), Setup & auth, and CLI errors: report an issue. Command details are authoritative in reference/ (dataset / finetune / deploy) and bl <command> --help — do not guess flags. Examples in reference/ stay bare; wrap with Call attribution when running. The whole pipeline requires an API key. If that protocol file is missing, stop and run bl skill init; do not guess auth/consent.
Call attribution: Examples below and in reference/ stay bare bl …. When running a command, wrap it with bailian-protocol → Call attribution (bash or PowerShell). One sample for this skill (BAILIAN_SKILL_NAME=bailian-finetune; replace codex with this host). After deploy, bl text chat is owned by bailian-cli.
BAILIAN_CALLER_TYPE=agent BAILIAN_CALLER_NAME=codex BAILIAN_SKILL_NAME=bailian-finetune BAILIAN_SKILL_VERSION=2.5.0 bl dataset validate --file train.jsonl
End-to-end workflow (follow in order)
1. Validate data bl dataset validate --file train.jsonl [--schema chatml|dpo|cpt|tts|image]
2. Upload data bl dataset upload --file train.jsonl # returns a file-id
3. Create job bl finetune text|audio|image create --base-model <base> --datasets <file-id|path>
4. Watch progress bl finetune watch --job-id ft-xxx # or get / logs
5. Pick artifact bl finetune checkpoints --job-id ft-xxx
6. Export model bl finetune export --job-id ft-xxx --checkpoint ckpt-N --model-name my-model
7. Compress model bl finetune compress templates --model my-model # optional; full-parameter models only
bl finetune compress create --model my-model --template-id <template-id>
bl finetune compress watch --job-id quant-xxx --follow
8. Deploy service bl deploy text|audio|image create --model-name <my-model|quantized-output> --display-name my-svc
What ships with it
4 files 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.
- today Changed 80906b5782bf
- yesterday Changed 42e813e1a117
- 2d ago Changed 0df84d4c2fd9
- 6d ago Changed · +6 lines 7c94795f0ec7
- 7d ago Changed 0abe9e85fc59
- 9d ago Changed 83acd9201e01
- 10d ago Changed 962a9b79ae14
- 11d ago Changed 78adfbe186b1
- 13d ago Changed 701aac5ac7f9
- 15d ago First seen · 95 lines · 250 tokens per session scan A 746ca2698727
bailian-finetune is a skill published in the GitHub repository modelstudioai/cli (366 stars, last pushed today), licensed Apache-2.0. It adds 250 tokens to every session and 2,150 once invoked, about $0.0010 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.
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