CD dream-interpreter
解梦技能（周公解梦 + 心理学双轨解读）。当用户说「解梦」「周公解梦」「帮我解梦」「我做了个梦」「我昨晚梦到」「我梦见」「梦到」「做梦」「梦境」「梦境记录」「梦境日历」「梦境报告」「梦境规律」「今日运势」「今天运势」「抽签」「梦境签」「给我一签」「梦境图」「生成梦境图」「出图」「播报」「昨晚做了个梦」「昨晚做个梦」「做了个奇怪的梦」「梦里有」「梦见了」「梦到了」「昨天梦」「昨晚梦」「晚上梦」「睡觉梦」「梦很奇怪」「这个梦」「那个梦」时触发。
As a process D 40/100 · 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 files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
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 · 2
-
high Secrets in code
secret-google-keySKILL.md:397Google API key--api-key AIza…QVg
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:397High-entropy token-like string (may be an id, hash or a credential)--api-key AIza…QVg
Files scanned: 3. 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 40/100
- 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
- 40Consistency. Frontmatter name (dream-interpreter) differs from the folder (dreaminterpreter)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4157 tokens
- 100Steps. 195 steps
- 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
- +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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -2localhost URLs: will not work for another user
- -232 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 222: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 195 items
- +4Has examples (21 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.