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ssy-batchjob-async-jobssy 批处理异步作业

Agent Skill

ssy-batchjob-async-job 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ssy-batchjob-async-job(ssy 批处理异步作业)
来源仓库:https://github.com/cocovs/ssy-batchjob-async-job
安装命令:
openclaw skills install ssy-batchjob-async-job
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ssy-batchjob-async-job

简介

通过 BatchJob API 实现文件上传与异步作业管理。

  • 支持预检、提交、轮询与取消全流程自动化。
  • 适用于大文件处理与后台任务调度场景。ssy-batchjob-async-job 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install ssy-batchjob-async-job。
  • 需对接目标 API 服务并配置认证参数。

SKILL.md

name
batchjob-async-job
description
Use BatchJob HTTP APIs for strict upload validation, precheck, submit, polling, and cancellation. Full-auto file source resolution (file_id/local path/public URL/channel attachment path) with fallback interaction only when source is not readable.
metadata
{ "openclaw": { "emoji": "🧪", "requires": { "bins": ["curl"], "env": ["BATCHJOB_BASE_URL", "BATCHJOB_BEARER_TOKEN"] } } }

BatchJob Async Job Skill

Use this skill when the user wants to run or manage batch jobs through the BatchJob service.

Required Environment

  • BATCHJOB_BASE_URL
  • BATCHJOB_BEARER_TOKEN

All HTTP requests must include:

-H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}"
-H "Content-Type: application/json"

API Endpoints

  • POST /v1/batch/files:upload
  • POST /v1/batch/jobs:precheck
  • POST /v1/batch/jobs
  • GET /v1/batch/jobs/{job_id}
  • GET /v1/batch/jobs?page=1&page_size=10&status=...
  • POST /v1/batch/jobs/{job_id}:cancel

Automation Policy (Default)

  • Always run in full-auto mode.
  • Do not ask user for file_id first.
  • Resolve file source from current message/context, then upload automatically when needed.
  • Ask follow-up questions only when no readable file source can be obtained.
  • Accepted input file formats for upload: jsonl, csv, xlsx, xls (BatchJob normalizes to internal JSONL).
  • For jsonl, each line must be either:

- canonical Vertex format (contents + optional generationConfig) - simple prompt format (prompt + optional aspect_ratio / image_urls, where image_urls must be publicly reachable URLs)

  • If user gives only model mode after a file message, treat it as confirmation and continue automatically.

Guardrails (Must Follow)

  • Do not auto-retry by creating a second job unless user explicitly asks.
  • Do not auto-rewrite dataset format after a terminal failure unless user explicitly asks.
  • Before upload, auto-normalization is allowed only once for known safe mappings (e.g. simple prompt JSONL -> Vertex JSONL).
  • Upload failure is terminal for this run: do not continue to precheck/submit when upload fails.
  • Never submit when row_count <= 0.
  • Do not fetch or parse output_summary_url automatically; only do it when user asks for detailed failure reason.
  • After reaching terminal status (completed, failed, partially_failed), stop execution and return summary immediately.

JSONL Compatibility Rule (Important)

BatchJob internal execution expects each JSONL line to be a VertexGeminiImageRequest shape.

  • Canonical line format:

- contents[0].parts[0].text contains prompt text - generationConfig.imageConfig.aspectRatio is optional - generationConfig.responseModalities should include IMAGE and TEXT

  • Non-canonical simple JSONL like {"prompt":"...","aspect_ratio":"1:1"} is acceptable; server will normalize it to Vertex format.
  • If JSONL has neither contents nor prompt, stop and ask user to provide valid data.
  • Explicitly unsupported (must reject before submit):

- OpenAI Batch style lines containing method + url + body (for example /v1/chat/completions payload). - This schema will fail with Vertex error: at least one contents field is required.

Dataset Output Rule (Important)

When user asks you to generate a template/demo file for BatchJob image tasks:

  • Prefer CSV headers: prompt,aspect_ratio,image_urls
  • Or JSONL line format with prompt / aspect_ratio / image_urls
  • If image_urls is provided, it must be publicly accessible (http/https).
  • Do NOT generate OpenAI batch envelope (custom_id + method + url + body) as final upload file

User Template Response (Important)

When user asks for format/template, return:

  1. A short explanation (prompt required, aspect_ratio/image_urls optional, and image_urls must be public URLs).
  2. One copyable CSV snippet (default).
  3. Optionally one JSONL snippet (simple prompt schema).
  4. Local template file paths (if available):

- /home/node/.openclaw/workspace/templates/batchjob-input-template.csv - /home/node/.openclaw/workspace/templates/batchjob-input-template.jsonl - /home/node/.openclaw/workspace/templates/batchjob-format-guide.md

Do not output OpenAI batch envelope examples in template replies.

File Source Resolver (Strict Order)

  1. Existing file_id:

- if provided, skip upload.

  1. Public file_url (http:// or https://):

- download to temp local file, then upload.

  1. Explicit local file_path:

- if readable, upload.

  1. Inbound attachment local path from channel/runtime context:

- examples: /tmp/..., MEDIA:<path>, /tmp/openclaw-media/.... - if readable, upload.

  1. Channel private file token/object (no local path, no public URL):

- if runtime has a channel adapter that can download attachment bytes, use it and upload. - if not available, enter fallback interaction.

Resolver output must be normalized to one of:

  • file_id
  • file_path (readable local file)

Execution Flow

  1. Confirm model and mode; if missing, use safe defaults (model=google/gemini-2.5-flash-image, mode=fast) and tell user.
  2. Resolve file source using resolver above.
  3. If resolver gives file_path, upload via POST /v1/batch/files:upload to get file_id.

- For .jsonl, inspect a few non-empty lines first: - if contents exists, upload as-is. - if only prompt/aspect_ratio/image_urls exists, upload as-is (server will normalize). - if method + url + body exists, stop and ask user to switch to BatchJob schema. - if structure is unknown, stop and ask user for valid schema. - Backward compatibility fallback: - if upload fails with unsupported file type for csv/xlsx/xls, convert once to JSONL and retry upload once. - do not retry more than once. - If upload returns validation error (unsupported schema, no valid data rows), stop immediately and return fix guidance.

  1. Run precheck with record_count (prefer uploaded file row_count).
  2. Submit job with file_id.
  3. Poll job status until terminal (completed, failed, partially_failed) with bounded timeout:

- interval: 5 seconds - max polls: 12 (about 60 seconds) - if still non-terminal after max polls: return current status and job_id, then stop.

  1. Return concise summary with job_id, status, progress, and output_summary_url.

When user only asks for estimate, stop at precheck and do not submit.

Fallback Interaction (Only When Needed)

Use this when resolver cannot read file bytes from current channel/context:

我拿到了“文件引用”,但当前运行环境无法直接读取该附件内容。请任选其一: 1) 直接发一个可公网下载的 URL 2) 提供本机可读路径(如 /tmp/xxx.csv) 3) 先把文件上传到 BatchJob,给我 file_id

If the current channel supports resending as direct attachment path in context, also ask user to resend once.

File Source Playbook

A) Public URL -> Local Temp File

FILE_URL="https://example.com/input.jsonl"
EXT="${FILE_URL##*.}"
FILE_PATH="$(mktemp "/tmp/batchjob-input.XXXXXX.${EXT:-jsonl}")"
curl -fL --retry 3 --connect-timeout 10 "$FILE_URL" -o "$FILE_PATH"

A2) JSONL Schema Sanity Check

Use this before upload to avoid wrong schema submission.

SRC_JSONL="/tmp/input.jsonl"
FIRST_LINE="$(grep -m1 -v '^[[:space:]]*$' "$SRC_JSONL")"
echo "$FIRST_LINE" | jq -e '
  (has("contents")) or
  (has("prompt")) and ( (has("method")|not) and (has("url")|not) and (has("body")|not) )
' >/dev/null || {
  echo "JSONL schema invalid for BatchJob: requires contents or prompt-only schema"
  exit 1
}

B) Feishu/Channel Attachment Path

If message context already includes local attachment path, treat it as FILE_PATH directly.

FILE_PATH="/tmp/openclaw-media/your-uploaded-file.jsonl"

If only a channel token/link is provided but no downloadable URL and no local path, try channel adapter download first. If adapter is unavailable, use fallback interaction.

Curl Templates

FILE_PATH="/path/to/input.jsonl"
FILE_NAME="$(basename "${FILE_PATH}")"
test -f "${FILE_PATH}" || { echo "文件 ${FILE_PATH} 不存在"; exit 1; }
FILE_CONTENT_B64="$(base64 < "${FILE_PATH}" | tr -d '\
')"

curl -sS "${BATCHJOB_BASE_URL}/v1/batch/files:upload" \
  -H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}" \
  -H "Content-Type: application/json" \
  -d "{\"filename\":\"${FILE_NAME}\",\"mode\":\"fast\",\"content\":\"${FILE_CONTENT_B64}\"}"
curl -sS "${BATCHJOB_BASE_URL}/v1/batch/jobs:precheck" \
  -H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{"record_count": 100, "model": "google/gemini-2.5-flash-image", "mode": "fast"}'
curl -sS "${BATCHJOB_BASE_URL}/v1/batch/jobs" \
  -H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{"file_id": "your-file-id", "model": "google/gemini-2.5-flash-image", "mode": "fast"}'
curl -sS "${BATCHJOB_BASE_URL}/v1/batch/jobs/${JOB_ID}" \
  -H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}"
curl -sS "${BATCHJOB_BASE_URL}/v1/batch/jobs/${JOB_ID}:cancel" \
  -H "Authorization: Bearer ${BATCHJOB_BEARER_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{"reason":"user requested cancellation"}'

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

84.4%
按下载量换算2,942

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install ssy-batchjob-async-job 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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