AF financial-report-analyzer
EN: Extract, normalize and analyze key metrics from corporate financial reports (10-K, 10-Q, A-share annual/interim reports, IFRS/GAAP/CAS PDFs). Produces side-by-side YoY/QoQ comparisons, ratio analysis (ROE/ROA/gross margin/debt ratio/cash conversion cycle), and red-flag detection (earnings management signals, related-party tx anomalies, goodwill risk). Use when user uploads or names a financial report and asks "解读 / 分析 / 拆解 / 找风险点 / 对比同行 / extract financials". 中文：从企业财报（10-K、10-Q、A股年报半年报、IFRS/GAAP/CAS PDF）中抽取并归一化关键指标，输出同比/环比对比、关键比率分析（ROE/ROA/毛利率/资产负债率/现金转换周期），以及红旗信号检测（盈余管理迹象、关联交易异常、商誉风险）。当用户上传或提及财报并要求"解读/分析/拆解/找风险点/同行对比"时触发。
EN: Extract, normalize and analyze key metrics from corporate financial reports (10-K, 10-Q, A-share annual/interim reports, IFRS/GAAP/CAS PDFs).
As a process F 45/100 · Will not run — References files that are not bundled: scripts/normalize_statements.py
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/normalize_statements.py
Process rating: all ten parameters 45/100
- 0Tools and files. 1 referenced file(s) missing: scripts/normalize_statements.py
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 40Consistency. Frontmatter name (financial-report-analyzer) differs from the folder (financial-report-analyzer-pro)
- 50When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 45 steps
- 100Execution cost. Instruction body is 1488 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
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)
- -214 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 634: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 45 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.