BB alibabacloud-agentloop-contextstore
Operate Alibaba Cloud CloudMonitor Service (CMS) AgentLoop ContextStore by using aliyun CLI with api version 2024-03-30. Use when users mention CloudMonitor, CMS, AgentLoop, agent loop, context, memory, experience, ContextStore, context store, 上下文库, 记忆库, 经验库, or ask to create/query/update/delete stores, write/search/update/delete context records, manage store API keys, or debug aliyun cms ContextStore commands.
As a process B 67/100 · Nearly there — weak spots: result and completion
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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
- 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 · 5
✓ No critical or high findings
Medium and low: 5
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:30Privilege escalation / world-writable permissionssudo mv aliyun /usr/local/bin/
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:45Privilege escalation / world-writable permissionssudo mv aliyun /usr/local/bin/
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:58Privilege escalation / world-writable permissionssudo mv aliyun /usr/local/bin/
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:71Privilege escalation / world-writable permissionssudo mv aliyun /usr/local/bin/
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medium Dangerous commands
cmd-pipe-to-shellSKILL.md:23Downloads and executes remote code from an unrecognised host (pipe to shell) (quoted — discussed, not commanded)> Run `aliyun version` to verify >= 3.3.3. If not installed or version too low, run `curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash` to install/update, or see `references/cli-installation-gui
quoted
Files scanned: 9. 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 67/100
- 0Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 25 steps, 1 vague phrases
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3407 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 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
- +1No license
- +2Single-language instructions
- +3Description length 414: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.