bytedance/agentkit-samples is a collection of examples and tutorials for Volcengine AgentKit, an AI-agent development platform for building, deploying, and operating agent applications. Developers use the samples to learn agent creation, multi-agent collaboration, memory, retrieval, MCP integrations, media generation, customer service, and other workflows. The catalogue skills provide agent workflows based on these examples.
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 bytedance/agentkit-samples --skill byted-sol-stability-sli-modelinggit clone --depth 1 https://github.com/bytedance/agentkit-samplesWrote 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/bytedance/agentkit-samples/byted-sol-stability-sli-modeling)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-sol-stability-sli-modeling"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-sol-stability-sli-modeling/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/bytedance/agentkit-samples/byted-sol-stability-sli-modeling"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-sol-stability-sli-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.00471 |
| Opus 5 | $0.00015 | $0.00235 |
| Sonnet 5 | $0.00006 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
byted-sol-stability-sli-modeling 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 6d 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
SLI Modeling Skill
输入
- 能力/场景描述文本（必填）
- owner（必填）
- 参考文档路径（选填）
输出
固定输出到 output/<slug>/：
sli-spec.jsonsli-report.md
SLI Spec 字段（强约束）
capabilityuser_journeysli_namesli_type：availability|latency|correctness|freshness|completeness|consistencymeasurementdenominatordimensiontarget_sloerror_budgetseverity：P0|P1|P2owner
执行规则
- 不得输出缺失字段的 SLI Spec。
sli_type与severity必须命中枚举。- 字段校验失败必须返回可诊断错误，不静默补全无意义默认值。
- 允许通过输入文本中的
key: value形式显式指定字段并覆盖推断。 - 优先围绕关键用户旅程建模（如登录、核心请求、结算），避免使用 CPU/内存等内部资源指标直接充当 SLI。
- 优先采用 request-based 口径（good requests / total requests）；确有需要时才采用 period-based 口径，并在
target_slo中显式说明窗口。 - 默认使用 rolling 30d 目标窗口，
error_budget默认遵循1 - target_slo的口径。 - 不使用 100% 作为默认目标；建议使用 99.x 目标并通过 burn-rate 观察预算消耗。
CLI
byted-sol-stablity-sli-modeling \
--input examples/input.capability.md \
--owner team-observability \
--out-dir output
What ships with it
8 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.
- LICENSE 1.0 KB
- prompt.md 1.0 KB
- pyproject.toml 443 B
- src/sli_modeling_skill/__init__.py 212 B runs code
- src/sli_modeling_skill/cli.py 1.4 KB runs code
- src/sli_modeling_skill/exporter.py 1.4 KB runs code
- src/sli_modeling_skill/modeler.py 5.0 KB runs code
- src/sli_modeling_skill/models.py 2.5 KB runs code
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.
- 6d ago First seen · 55 lines · 31 tokens per session scan A 665c16ddb162
byted-sol-stability-sli-modeling is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 5d ago), licensed Apache-2.0. It adds 31 tokens to every session and 471 once invoked, about $0.0002 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 2026-09-03.
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