SKILLEMALL.ai

AD enterprise-report-merger

企业报表合并技能。将多个 Excel/PDF/图片格式的企业报表(财务三大表、部门预算表、业务数据表等)按指定模式合并为统一报表,并将合并结果无缝嵌入 Word 模板生成专业报告。内置三种合并策略:多表纵向堆叠、关键科目映射匹配、合并报表+抵销分录。当用户明确要求生成分析报告(如贷后分析报告)且无模板时可自动构建含财务比率、风险评估与战略建议的完整分析报告。触发词:合并报表、汇总报表、填入Word模板、集团合并报表。

ClawHub Claude Code author: Merlinbeard000 v1.1.1 MIT-0 11 files body ≈ 3 348 tokens Open the sourceclawhub.ai analyzed 3 d ago

企业报表合并技能。将多个 Excel/PDF/图片格式的企业报表(财务三大表、部门预算表、业务数据表等)按指定模式合并为统一报表,并将合并结果无缝嵌入 Word…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordExcelData and analyticsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 11. 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")
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 62 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3348 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 210: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 62 items
  • +4Has examples (19 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This is a disclosed local financial-report merging skill with no evidence of hidden access, exfiltration, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 21 Aug 2026