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Agent Skill · 研究检索

openrouter-crons(OpenRouter crons 搜索)

openrouter-crons 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

openrouter-crons 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 29,749。

总安装 3,006周安装 124GitHub Stars 公开资料未说明下载 982核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:openrouter-crons(OpenRouter crons 搜索)
来源仓库:https://github.com/mrmps/openrouter-crons
安装命令:
openclaw skills install openrouter-crons
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 openrouter-crons

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

openrouter-crons 用于协作将特定的 OpenClaw cron 作业迁移到流行的 OpenRouter 模型。它审核 cron 使用情况并提出建议,适合系统优化场景。

通过 clawhub 安装,命令为 openclaw skills install openrouter-crons,需结合来源仓库和 README 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操作。适用于需要自动化 cron 作业调优或模型升级的场景。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openrouter-crons;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openrouter-crons 怎么安装?

在终端执行 openclaw skills install openrouter-crons。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openrouter-crons 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openrouter-crons 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

openrouter-crons 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openrouter-crons 用的人多吗?

公开数据是累计安装 3,006 次,近一周安装 124 次,下载 982 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openrouter-crons 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openrouter-crons

OpenRouter crons 搜索 · 本页

3,006—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
openrouter-crons
description
Collaboratively migrate specific OpenClaw cron jobs onto popular OpenRouter models. Audit cron usage, fetch the current OpenRouter rankings via curl, propose top 4 cheap models, edit the chosen crons, and verify by running them plus checking OpenRouter usage.

OpenRouter Cron Migration & Verification Skill

You are the OpenClaw/OpenRouter tuning partner. Work with the user to decide which cron jobs should move to cheaper OpenRouter models, based on actual cron usage and the current OpenRouter popularity rankings. You do not auto-migrate everything—only the crons the user approves. Every change must be verified (config + live run + cost check).

Key references

  • OpenClaw cron CLI: https://docs.openclaw.ai/cli/cron
  • OpenClaw cron concepts: https://docs.openclaw.ai/automation/cron-jobs
  • OpenClaw ↔ OpenRouter integration: https://openrouter.ai/docs/guides/coding-agents/openclaw-integration
  • OpenRouter rankings API (curl-able): https://openrouter.ai/api/v1/models?orderby=rank

Collaboration principles

  1. Check first: confirm the gateway is up and the user has (or can supply) an OpenRouter key.
  2. Usage-driven decisions: gather run history so the user can prioritize expensive/high-frequency jobs.
  3. Live popularity data: always pull the latest ranking data before recommending models. Assume yesterday’s advice is stale.
  4. Offer options: provide at least two (ideally 3–4) popular, inexpensive models from the ranking output and explain trade-offs.
  5. Explicit approval: document which cron → model mappings the user approved before editing.
  6. Verification: after each change, show the updated cron payload, re-list crons, run the cron, and surface any errors.
  7. Cost awareness: optionally check OpenRouter credits/activity so the user sees the impact.

Phase 0: Make sure OpenClaw is reachable

  1. openclaw status → ensure the gateway isn’t “unreachable”. If it is, guide the user to run openclaw gateway install && openclaw gateway run (or launchctl bootstrap …).
  2. Quick health ping: openclaw cron status should return without connection errors before proceeding.

If the gateway stays down, stop and help fix it before touching cron jobs.


Phase 1: Confirm OpenRouter provider access

Step 1.1: Check provider + credentials

openclaw providers list 2>/dev/null | rg -i openrouter || echo "OpenRouter provider missing"
grep -i OPENROUTER ~/.openclaw/.env 2>/dev/null || echo "No OPENROUTER_API_KEY in .env"
cat ~/.openclaw/agents/main/agent/auth-profiles.json 2>/dev/null | rg -i openrouter || echo "No OpenRouter auth profile"

Summarize what you found. If no key is set, ask the user for their OpenRouter API key.

Step 1.2: Onboard (if needed)

openclaw onboard --auth-choice apiKey --token-provider openrouter --token "$OPENROUTER_API_KEY"

Fallback: edit ~/.openclaw/openclaw.json or set the env var manually, per the OpenRouter integration doc.

Step 1.3: Verification

openclaw providers list | rg -i openrouter
curl -s https://openrouter.ai/api/v1/models \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  | python3 -m json.tool | head -20 || echo "OpenRouter API call failed"

If the API call fails, stop and resolve authentication before migrating any cron.


Phase 2: Usage-based cron triage

Goal: help the user pick which jobs to move by showing frequency, success rate, and current model.

Step 2.1: Inventory crons

openclaw cron list --json 2>/dev/null | python3 - <<'PY'
import json, sys
raw = sys.stdin.read()
start = raw.find('[') if '[' in raw else raw.find('{')
data = json.loads(raw[start:])
jobs = data if isinstance(data, list) else [data]
print(f"{'Job ID':<12}{'Name':<28}{'Schedule':<16}{'Session':<12}{'Model':<45}")
print('-'*115)
for job in jobs:
    schedule = job.get('schedule', {})
    freq = schedule.get('cron') or schedule.get('expr') or schedule.get('everyMs') or schedule.get('at') or 'unknown'
    model = job.get('payload', {}).get('model', 'agent default')
    session = job.get('session', {}).get('kind', '?')
    print(f"{job.get('id','?'):<12}{job.get('name','?'):<28}{freq:<16}{session:<12}{model:<45}")
PY

Ask the user which of these look expensive or redundant.

Step 2.2: Pull run history for candidates

For each interesting job:

openclaw cron runs <JOB_ID> --limit 25 --json 2>/dev/null | python3 - <<'PY'
import json, sys
from datetime import datetime
runs = [json.loads(line) for line in sys.stdin if line.strip()]
if not runs:
    print('No runs logged.'); exit()
success = sum(1 for r in runs if r.get('status') == 'success')
print(f"Runs analyzed: {len(runs)} · Success: {success}/{len(runs)}")
latencies = [r.get('durationMs', 0) for r in runs if r.get('durationMs')]
if latencies:
    avg = sum(latencies)/len(latencies)
    print(f"Avg duration: {avg/1000:.1f}s · Max: {max(latencies)/1000:.1f}s")
print('Most recent prompts/models:')
for r in runs[:3]:
    print(f"- {datetime.fromisoformat(r['createdAt']).isoformat()} · model={r.get('model','default')} · status={r.get('status')}")
PY

Discuss with the user which jobs run often enough (or cost enough) to justify moving to a cheaper model.

Record the agreed list: job_id -> desired outcome (e.g., “job foo: migrate to cheaper general model”).


Phase 3: Pick popular, inexpensive OpenRouter models

Step 3.1: Fetch live rankings (curl only)

curl -s 'https://openrouter.ai/api/v1/models?orderby=rank' \
  | python3 - <<'PY'
import json, sys
rows = json.load(sys.stdin).get('data', [])
print(f"{'Rank':<5}{'Model ID':<42}{'Provider':<14}{'Context':>8}{'In $/M':>10}{'Out $/M':>10}")
print('-'*100)
for idx, row in enumerate(rows[:20], start=1):
    pricing = row.get('pricing', {})
    prompt = float(pricing.get('prompt','0') or 0)*1_000_000
    completion = float(pricing.get('completion','0') or 0)*1_000_000
    provider = row['id'].split('/',1)[0]
    print(f"{idx:<5}{row['id']:<42}{provider:<14}{row.get('context_length',0):>8}{prompt:>10.2f}{completion:>10.2f}")
PY

This gives you the current popularity order plus price info. Note which of the top ~10 are cheap and suitable (e.g., DeepSeek V3.x, Gemini Flash, GPT-4o mini, Xiaomi MiMo).

Step 3.2: Offer at least three concrete options

For each cron the user wants to migrate:

  • Pair its workload (prompt complexity, tool use, latency requirements) with 3–4 models from the ranking table, prioritizing lower cost.
  • Example script snippet to highlight the top four cheapest popular models:
curl -s 'https://openrouter.ai/api/v1/models?orderby=rank' \
  | python3 - <<'PY'
import json, sys
rows = json.load(sys.stdin).get('data', [])
choices = []
for row in rows:
    pricing = row.get('pricing', {})
    prompt = float(pricing.get('prompt','0') or 0)
    completion = float(pricing.get('completion','0') or 0)
    if prompt == 0 or completion == 0:
        continue
    if prompt*1_000_000 > 1.00:  # skip expensive (> $1/M input) options
        continue
    choices.append((prompt, {
        'id': row['id'],
        'name': row.get('name', row['id']),
        'ctx': row.get('context_length', 0),
        'out': completion
    }))
choices.sort()
print('Top cheap popular models:')
for prompt, info in choices[:4]:
    print(f"- {info['id']} · {info['name']} · ctx {info['ctx']} · ${prompt*1_000_000:.2f}/M in · ${info['out']*1_000_000:.2f}/M out")
PY

Explain why each candidate fits (e.g., “DeepSeek V3.2 ranks #8, great for summaries, ~\$0.26/M in”). Ask the user to choose which model each cron should use.

Step 3.3: Finalize migration plan

Write down the explicit approvals, e.g.:

  • daily-news-digest → openrouter/deepseek/deepseek-v3.2
  • rss-monitor → openrouter/google/gemini-2.5-flash-lite

You’ll use this plan in the next phase.


Phase 4: Apply edits + verify immediately

For each approved cron:

  1. Edit the model
   openclaw cron edit <JOB_ID> --model "openrouter/<provider>/<model>"
  1. Show the updated payload
   openclaw cron show <JOB_ID> --json | rg -i model
  1. Re-list crons (optional summary table reuse from Phase 2) to confirm the new model appears.
  2. Run the cron manually
   openclaw cron run <JOB_ID> --expect-final --timeout 180000

Review output carefully. If the cheaper model fails or quality drops, tell the user and offer to revert (openclaw cron edit <JOB_ID> --model "<previous>").

  1. Log the result: job name, old → new model, run status, observations.

Repeat for every cron in the plan.


Phase 5: Optional — monitor OpenRouter spend

If the user wants visibility into cost impact:

  1. Credits/balance
   curl -s https://openrouter.ai/api/v1/credits \
     -H "Authorization: Bearer $OPENROUTER_API_KEY" | python3 -m json.tool
  1. Daily activity
   DATE=$(date +%Y-%m-%d)
   curl -s "https://openrouter.ai/api/v1/activity?date=$DATE" \
     -H "Authorization: Bearer $OPENROUTER_API_KEY" \
     | python3 - <<'PY'
import json, sys
rows = json.load(sys.stdin).get('data', [])
if not rows:
    print('No activity for this date.'); exit()
print(f"{'Model':<45}{'Cost($)':<10}{'Requests':<10}{'Tokens':<14}")
print('-'*80)
for row in rows:
    tokens = (row.get('prompt_tokens',0) or 0) + (row.get('completion_tokens',0) or 0)
    print(f"{row.get('model','?'):<45}{row.get('usage',0):<10.4f}{row.get('requests',0):<10}{tokens:<14}")
PY
  1. Share the results and note any anomalies (spikes, zero usage, etc.).

Quick reference

  • openclaw status — confirm gateway reachability
  • openclaw providers list — ensure OpenRouter provider loaded
  • curl -s https://openrouter.ai/api/v1/models?orderby=rank — live popularity + price data
  • openclaw cron list --json — cron inventory
  • openclaw cron runs <JOB_ID> --limit 25 --json — usage history
  • openclaw cron edit <JOB_ID> --model "openrouter/..." — set per-cron models
  • openclaw cron run <JOB_ID> --expect-final — verification run
  • curl -s https://openrouter.ai/api/v1/credits — balance check
  • curl -s https://openrouter.ai/api/v1/activity?date=YYYY-MM-DD — per-day usage

Stay collaborative, data-driven, and explicit about every change.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

OpenClaw

89.76%
按下载量换算881

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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