CD session-archive-manager
智能管理OpenClaw会话文件 - 裁剪大session、生成智能总结、归档旧会话、清理空间。使用场景：session文件过大、需要释放磁盘空间、整理旧会话记录、自动定期归档。当用户提到"归档session"、"裁剪会话"、"清理session空间"、"整理旧会话"、"session太大"、"运行session归档"、"使用session归档skill"时，立即使用此skill。
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 7
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high Dangerous commands
cmd-persistencescripts/setup_cron.sh:37Persistence mechanism (cron / launchd / scheduled task / autorun registry)(crontab -l 2>/dev/null | grep -v "$SCRIPT_PATH"; echo "$CRON_JOB") | crontab -
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high Dangerous commands
cmd-persistencescripts/setup_cron.sh:41Persistence mechanism (cron / launchd / scheduled task / autorun registry)(crontab -l 2>/dev/null; echo "$CRON_JOB") | crontab -
Medium and low: 5
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low Dangerous commands
cmd-cron-mentionscripts/setup_cron.sh:30Mentions editing / listing crontabcrontab -l 2>/dev/null || echo "(暂无定时任务)"
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low Dangerous commands
cmd-cron-mentionscripts/setup_cron.sh:34Mentions editing / listing crontabif crontab -l 2>/dev/null | grep -q "$SCRIPT_PATH"; then
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low Dangerous commands
cmd-cron-mentionscripts/setup_cron.sh:37Mentions editing / listing crontab(crontab -l 2>/dev/null | grep -v "$SCRIPT_PATH"; echo "$CRON_JOB") | crontab -
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low Dangerous commands
cmd-cron-mentionscripts/setup_cron.sh:41Mentions editing / listing crontab(crontab -l 2>/dev/null; echo "$CRON_JOB") | crontab -
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low Dangerous commands
cmd-cron-mentionscripts/setup_cron.sh:47Mentions editing / listing crontab (string literal in code, not executed)echo "可以使用 'crontab -l' 查看当前任务"
code literal
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 922 tokens
- 100Running it twice. No mutating operations
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
- -31 of 7 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 192: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (15 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.