CC apm-performance-analysis
APM 性能分析工具，通过 ApmClient.SendMCPMessage 连接腾讯云 APM MCP Server，提供业务系统查询、调用链追踪、火焰图、Span 耗时分析等能力。Trigger when user mentions APM, 性能分析, 调用链, 火焰图, Span, or 耗时分析.
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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 · 9
✓ No critical or high findings
Medium and low: 9
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medium Dangerous commands
cmd-shell-rcreferences/credential_guide.md:30Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.zshrc
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medium Dangerous commands
cmd-shell-rcreferences/credential_guide.md:31Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_KEY="your-secret-key"' >> ~/.zshrc
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medium Dangerous commands
cmd-shell-rcreferences/credential_guide.md:58Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.zshrc
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medium Dangerous commands
cmd-shell-rcreferences/credential_guide.md:59Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_KEY="your-secret-key"' >> ~/.zshrc
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medium Dangerous commands
cmd-shell-rcreferences/credential_guide.md:66Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_ID="your-secret-id"' >> ~/.bashrc
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medium Exfiltration
net-redirectable-api-keyscripts/apm_mcp_client.py:178Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
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medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash Read
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low Dangerous commands
cmd-shell-rcscripts/apm_mcp_client.py:169Writes to a shell startup file (string literal in code, not executed)" echo 'export TENCENTCLOUD_SECRET_ID=\"your-secret-id\"' >> ~/.zshrc\n"
code literal -
low Dangerous commands
cmd-shell-rcscripts/apm_mcp_client.py:170Writes to a shell startup file (string literal in code, not executed)" echo 'export TENCENTCLOUD_SECRET_KEY=\"your-secret-key\"' >> ~/.zshrc\n"
code literal
Files scanned: 31. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 59/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 700 tokens
- 100Progress reporting. Reports progress
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
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 154: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.