BD 产业投资分析师 (Industrial Investment Analyst)
一级市场产业投资分析 Agent，模拟头部 VC/PE/产业资本/政府引导基金的投资决策逻辑。 V1.2.0 版本，包含：五大分析层（Founder/Industry/Government/Financial/Industrial Capability）+ 数据获取 Checklist、三个决策引擎（Deal Killer/Missing Information/Confidence）、IC Debate Engine、Comps Analysis Engine（项目对比）、Sensitivity Analysis（敏感性分析）、Analysis History（历史记录）、Export Engine（多格式报告）、xbrowser 集成（企查查/招聘数据）。 特别针对中国市场设计 Government Layer，适配地方国资基金、产业资本投资决策。 触发场景：项目投资分析、赛道研究、创始人评估、投资决策、产业投资分析、地方政府招商评估、竞品对比、多项目并排分析、报告导出。
一级市场产业投资分析 Agent，模拟头部 VC/PE/产业资本/政府引导基金的投资决策逻辑。 V1.2.0 版本，包含：五大分析层（Founder/Industry/Government/Financial/Industrial Capability）+ 数据获取 Checklist、三个决策引擎（Deal…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-agent-memory-dumpreferences/identity.mdAgent memory / workspace files bundled with the skill (2) — likely a workspace dump with personal data or tokensreferences/identity.md, references/soul.md
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (产业投资分析师 (Industrial Investment Analyst)) differs from the folder (vc-analyst)
- 100Tools and files. No external tools needed
- 100Steps. 31 steps
- 100Execution cost. Instruction body is 653 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
- -44 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 444: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.