BC feifei-companion
飞飞学伴v4.0 - 三位一体AI学习陪伴系统 | UCL共情学习法+HERMES动态学习+主动AI | 菲菲老师/小菲学姐/浩云学长联合辅导 | FeiFei Companion v4.0 - Trinity AI Learning Companion with UCL Empathic Learning & HERMES Dynamic Learning Loop
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 2. 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") - warning
body-longSKILL.md body ≈ 11777 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "brand"
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Execution cost. Instruction body is 11777 tokens: crowds the task out of the window
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 69 steps
- 100Consistency. Name and required fields are in place
- low 16 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
- -261 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 185: enough signal without eating the budget
- +4Structure: 66 headings
- +3Step-by-step instructions: 69 items
- +4Has examples (30 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.
External checks
ClawHub: suspicious
This is an instruction-only tutoring skill, but it asks to build long-term profiles and parent-facing reports about children without clear consent or retention limits.
LLM: suspicious (high) · VirusTotal: · 29 May 2026