SKILLEMALL.ai

AC diagnose-scheduled-job-trigger-vs-execution-failure

用于排查“定时任务没执行”这类问题,并区分到底是未触发、已触发但执行失败,还是运行环境/授权失效导致的假象。遇到 cron 异常、任务未跑、自动任务失灵、网关重启后要验证恢复、怀疑是模型导致任务失败、需要查看日志作证、需要给出证据口径、要确认 `deactivated_workspace` / OAuth token 失效 / timeout 是否为根因时,都应触发本技能。也适用于“任务其实有 run 记录,但结果是 error”“想确认调度正常还是执行链路坏了”“修复授权后要做回归验证”等场景。

ClawHub Agent Skills author: can4hou6joeng4 v1.0.0 MIT-0 3 files body ≈ 1 935 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 58/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 4 mutating operations with no state check
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 75 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1935 tokens
    • medium 4 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 251: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 75 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a purpose-aligned OpenClaw scheduling and notification guide, with disclosed local cron edits and test notifications.
    LLM: benign (medium) · VirusTotal: · 29 May 2026