BC csv-analyzer
用简单命令分析CSV文。支持自动化配置和灵活的参数设置,适适用于不同工作场景,改善操作效率。CSV数据分析器工具。支持自动化配置和灵活的参数设置,适用于多种工作场景,提升工作效率和准确性。CSV数据分析器是一款高效实用的工具。csv-analyzer支持多种配置选项。Use when 需要数据分析、报表生成、统计洞察、数据可视化时使用。不适用于实时流数据处理。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
This is a copy of a skill from another catalog; the rating counts the canonical one: csv-analyzer (ClawHub)
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Map keys must be unique at line 25, column 1: category: Automation homepage: "" ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-long-hermesdescription is 181 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "summary_zh" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
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. Tools declared in frontmatter
- 100Steps. 33 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1768 tokens
- 100Running it twice. No mutating operations
- low 13 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
- +2Single-language instructions
- +3Description length 181: enough signal without eating the budget
- +4Structure: 47 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (11 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.
External checks
ClawHub: clean
This CSV-analysis skill is purpose-aligned and low risk, though its documentation is incomplete and users should be careful with output files.
LLM: benign (high) · VirusTotal: · 22 Aug 2026