SKILLEMALL.ai

AC historical-data-compare-claw

历史数据比对虾 — 专注于环比、同比、趋势等数据差异分析。激活场景:当用户提供两期或多期历史数据(Excel/CSV/数据库导出等),要求进行同比分析、环比分析、趋势对比、差异排查、变动归因、KPI变动说明、或"和上个月比怎么样"、"今年比去年如何"等数据对比类问题时触发。也适用于多维度数据切片对比(按区域、品类、渠道等维度拆解差异)。核心价值:趋势洞察——翻阅历史记录,清晰告诉决策者当下的变量。触发关键词:同比、环比、趋势、对比、差异、变动、变化、涨跌、增减、和上期比、和去年同期比、period over period、YoY、MoM、QoQ、同比分析、环比分析、趋势分析、数据对比。

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 4 files body ≈ 554 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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-when description 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. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 554 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 296: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This skill is a straightforward local data comparison helper for Excel or CSV files, with no evidence of hidden network access, credential use, or persistence.
LLM: benign (high) · VirusTotal: · 29 May 2026