BC 定向技术方案深度拆解调研
Comprehensive deep technical research on vendor-specific technical solutions/products. Standardized output covering four core modules: Hardware Breakdown, Software Breakdown, Hardware-Software Co-Design, and Technical Benchmarking. Strictly distinguishes publicly verifiable facts from technical derivations, enabling progressive deep-diving from overall architecture down to core components/algorithms. This Skill orchestrates research logic, information analysis, and report generation. Actual scraping tasks are delegated to web-scraper and playwright-scraper. Use when user asks to research a specific technical solution, product architecture, vendor technology breakdown, or needs deep technical analysis with fact/derivation distinction. Trigger phrases include: 调研技术方案, 拆解某个产品技术, 分析某公司技术方案, 深度调研某产品, technical solution research, vendor technology breakdown, product architecture deep-dive, hardware software co-design analysis.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Comprehensive deep technical research on vendor-specific technical… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "references"
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 10 mutating operations with no state check
- 40Consistency. Frontmatter name (定向技术方案深度拆解调研) differs from the folder (targeted-tech-research)
- 70Execution cost. Instruction body is 4052 tokens
- 100Tools and files. No external tools needed
- 100Steps. 106 steps
- 100Failures and branches. 9 branches, has a failure section
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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)
- +3Description length 934: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 26 headings
- +3Step-by-step instructions: 106 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.