BC meme-token-analyzer
Meme 代币财富基因检测系统。输入任意代币名称（如 PEPE、DOGE、$SHIB），基于实时 Web 情绪数据输出四维分析报告与 🌟钻石手/🌙登月/🗑️纸手/💩屎币 评级。支持主流币自动识别（BTC/ETH/SOL），无数据时不幻觉。触发词：meme 分析、代币评级、财富基因、PEPE分析、meme coin、rug check、meme token analyze、wealth gene、meme coin rating
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: 36. 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. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 546 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
- -36 of 6 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 219: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.
External checks
ClawHub: suspicious
The skill appears to be a meme-token analysis tool, but its package contains mismatched implementation paths and risky local helper/API surfaces that users should review before installing.
LLM: suspicious (medium) · VirusTotal: · 18 Jun 2026