BC model-advisor
智能模型选择顾问。根据任务类型（量化交易、代码编写、长文档处理、日常对话、隐私任务）自动推荐最优模型，平衡效率、质量和Token成本。触发场景：(1) 用户询问模型相关（"用什么模型"、"切换模型"、"模型推荐"、"最优模型"）；(2) 用户发起新任务时，主动分析任务类型并推荐最优模型；(3) 需要优化Token使用时。此技能应在每次新任务开始时主动触发，帮助用户选择最合适的模型。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 4. 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 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. 28 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1659 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
- +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
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 192: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 28 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.
External checks
ClawHub: suspicious
The skill appears to be a model-advice helper, but its reported auto-triggering and persistent preference recording are broader than users would reasonably expect.
LLM: suspicious (medium) · VirusTotal: · 16 Jul 2026