AD company-deep-analysis
A股/港股公司深度分析。输入公司名称或股票代码，自动完成 6 步分析流程： 数据采集 → 公司画像 → 产业链五力 → 竞争护城河 → 财务四维 → 相对估值。 输出双产物：公司深度分析报告 + 投研简报 支持单步模式：用户指定"财务情况/财务分析/公司画像/公司基本面"时，按路由表只跑对应步骤并输出对应单文件。 触发词：公司分析 / 深度分析 / 公司调研 / 投资初筛 / 深度调研 / 公司研究 / 行业研究 / 投研简报 / 财务情况 / 财务分析 / 公司画像 / 公司基本面
A股/港股公司深度分析。输入公司名称或股票代码，自动完成 6 步分析流程： 数据采集 → 公司画像 → 产业链五力 → 竞争护城河 → 财务四维 → 相对估值。 输出双产物：公司深度分析报告 + 投研简报 支持单步模式：用户指定"财务情况/财务分析/公司画像/公司基本面"时，按路由表只跑对应步骤并输出对应单文件。…
As a process D 44/100 · Unfinished process — 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.
- 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: 1. 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 44/100
- 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 (web, python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4172 tokens
- 100Steps. 109 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (7 tags): a typed call is more reliable
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 244: enough signal without eating the budget
- +4Structure: 42 headings
- +3Step-by-step instructions: 109 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 3 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.