AC tender-analyzer
投标文件全流程智能分析技能。解析招标/投标文件(PDF/DOCX/XLSX)，基于MECE原则进行多维度结构化需求拆解， 自动生成架构图/流程图/ER图/甘特图/雷达图五大专业图表，模拟评审专家打分并输出扣分明细， 根据评审意见逐条自动修订，提供类Git版本管理与迭代追踪。 Triggers: 投标, 招标, 标书分析, 需求拆解, 评审打分, 标书检查, 投标方案, 招标文件解析, 报价分析, 技术方案, 自动修改, bid, tender, RFP analysis, 标书版本管理, MECE分析.
投标文件全流程智能分析技能。解析招标/投标文件(PDF/DOCX/XLSX)，基于MECE原则进行多维度结构化需求拆解， 自动生成架构图/流程图/ER图/甘特图/雷达图五大专业图表，模拟评审专家打分并输出扣分明细， 根据评审意见逐条自动修订，提供类Git版本管理与迭代追踪。 Triggers: 投标, 招标…
As a process C 51/100 · Has gaps — 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: 14. 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") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 73 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2667 tokens
- low 14 top-level sections: this looks like several domains in one skill
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 254: enough signal without eating the budget
- +4Structure: 49 headings
- +3Step-by-step instructions: 73 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.