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-airesearch-videoevalgit 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-airesearch-videoeval)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-airesearch-videoeval"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-airesearch-videoeval/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-airesearch-videoeval"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-airesearch-videoeval.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 | $0.00086 | $0.02107 |
| Opus 5 | $0.00043 | $0.01053 |
| Sonnet 5 | $0.00017 | $0.00421 |
| Haiku 4.5 | $0.00009 | $0.00211 |
Grade A, and why
byted-airesearch-videoeval 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Byted Airesearch Videoeval
Use this skill to submit and query long-running material evaluation tasks.
When to use
Use this skill when the user wants to:
- evaluate a video material or creative asset
- submit a material evaluation task and get back a task identifier
- check the status of an existing evaluation task later
- fetch the final detail/result of a previously created evaluation task
Do not use this skill for generic video upload requests.
Current workflow
- Validate the full input batch before any upload starts.
- Upload the local video files and capture the returned
attachment_idvalues. - Create a task with the uploaded attachment IDs.
- Return success immediately after the task is created.
- Ask the user to query task list or task detail later if they want progress or results.
This workflow is intentionally non-blocking. Do not poll automatically after task creation.
Mandatory behavior
- Do not expose the upload API as a standalone user-facing capability.
- Do not trigger this skill for generic requests such as “upload this video”, “store this file”, or “send this video”.
- Only call the upload API when the user explicitly intends to create a new material evaluation task.
- For new task creation, prefer
scripts/submit_evaluation_task.pyso validation, upload, and task creation stay in one controlled flow. - Treat
scripts/upload_video.pyas an internal helper used by the orchestration flow, not as the primary user entrypoint. The script itself rejects direct use unless it is called with the internal orchestration marker.
For multi-file submissions, use the orchestration entrypoint so the whole batch is validated before the first upload starts.
Submission limits
- A single task can include at most 10 videos.
- Non-enabled users have a rolling free quota of at most 10 submitted videos within the last 24 hours.
- The new task's video count is added to the number of videos already submitted in the last 24 hours. If the total exceeds 10, the service rejects the task and asks the user to contact Volcengine sales to enable access.
- Enabled users are not restricted by this rolling 24-hour free quota.
- Quota accounting is based on the actual number of videos submitted per task, with no deduplication.
- Any task created within the last 24 hours counts toward the rolling quota, including running tasks.
- Login-based access and API key access share the same quota pool.
- The skill enforces the per-task limit locally before upload starts. The rolling 24-hour quota is enforced by the service, and the skill should surface the service rejection with a clear explanation.
What ships with it
7 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.
- 10d ago First seen · 201 lines · 86 tokens per session scan A 4f06d10cffcb
byted-airesearch-videoeval is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 6d ago), licensed Apache-2.0. It adds 86 tokens to every session and 2,107 once invoked, about $0.0004 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 skills, from other repositories
ensembl-database
Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.
aatmf-t10-confidentiality-breach
AATMF T10 — Integrity & Confidentiality Breach. System prompt extraction, training-data extraction, model-weight leakage, private-key recovery.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
sidewinder-rattlesnake
Adversary-emulation profile for SideWinder (G0121 / Rattlesnake / T-APT-04 / Razor Tiger), India's suspected state-sponsored cyber-espionage actor.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
sn-image-imitate
An image tool that creates new content while following the visual style and layout of a single reference image.