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AD openclaw-session-cleanup

Clean up accumulated subagent and cron:run child sessions in OpenClaw to fix slow subagent startup. Use when: subagents are slow to start, sessions.json is too large, too many child sessions have accumulated, session cleanup is needed, or the user mentions "session cleanup", "session compact", "clean sessions", "subagent slow", "sessions.json too large", "child session accumulation", "session too many", "subagent startup slow", "gateway slow". 清理 OpenClaw 积累的 subagent 和 cron:run child sessions，解决 subagent 启动慢的问题。 当用户提到 subagent 启动慢、session 太多、想清理 sessions、sessions.json 太大、child session 积累时，务必使用此 skill。

ClawHub Agent Skills author: lrddrl v1.0.1 MIT-0 2 files body ≈ 630 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: openclaw-session-cleanup (ClawHub)

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • 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 46/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 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
    • 40Consistency. Frontmatter name (openclaw-session-cleanup) differs from the folder (openclaw-subagent-session-cleanup)
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Execution cost. Instruction body is 630 tokens

    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
    • -215 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +3Description length 611: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 12 items
    • +4Has examples (4 code blocks)

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

    External checks

    ClawHub: suspicious
    This skill has a reasonable cleanup purpose, but it tells agents to run a missing cleanup script that can change session records and optionally delete conversation history.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026