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CC subagent-context-compactor

上下文压缩代理，采用分层压缩策略，基于内存使用触发机制。处理HOT/WARM/COLD三层数据，优化token使用。当用户需要压缩对话上下文、优化内存使用、管理会话历史、减少token消耗时使用此技能。特别适用于长时间对话、复杂任务处理、需要保留重要历史信息的场景。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: geoshan v1.0.0 MIT-0 26 files · 8 scripts body ≈ 1 073 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype 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
C
64/100
safety, quality, tests
Safety 60%
60
Quality 40%
71
Run on models
none yet
Process rating
C
53/100
Has gaps
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

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.

Dangerous commands
If you install

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.

For the author

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

  1. 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.
  2. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 6

  • high Dangerous commands cmd-persistence INSTALL.md:68
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "0 * * * * cd ~/.openclaw/workspace/skills/context-compactor && python3 integration.py --check") | crontab -
  • high Dangerous commands cmd-persistence INSTALL.md:71
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (crontab -l 2>/dev/null; echo "0 2 * * * cd ~/.openclaw/workspace/skills/context-compactor && find logs -name '*.log' -mtime +7 -delete") | crontab -
Medium and low: 4
  • low Dangerous commands cmd-cron-mention INSTALL.md:68
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "0 * * * * cd ~/.openclaw/workspace/skills/context-compactor && python3 integration.py --check") | crontab -
  • low Dangerous commands cmd-cron-mention INSTALL.md:71
    Mentions editing / listing crontab
    (crontab -l 2>/dev/null; echo "0 2 * * * cd ~/.openclaw/workspace/skills/context-compactor && find logs -name '*.log' -mtime +7 -delete") | crontab -
  • low Dangerous commands cmd-background-process start_monitor.sh:26
    Starts a background / autostarted process
    nohup python3 monitor.py >> "$LOG_FILE" 2>&1 &
  • low Dangerous commands cmd-background-process start_system.sh:97
    Starts a background / autostarted process
    nohup python3 integration.py >> "$LOG_DIR/integration.log" 2>&1 &

Files scanned: 26. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 43 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1073 tokens
  • 100Running it twice. No mutating operations
  • low 14 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -214 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 133: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 43 items
  • +4Has examples (16 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This appears to be a real context-compaction tool, but it needs Review because it can run background services that read and store OpenClaw workspace memory and manage local processes.
LLM: suspicious (high) · VirusTotal: · 29 May 2026