BF 小果可转债量化分析助手
小果(微信:xg_quant)可转债量化分析助手专注于可转债量化分析工具，基于小果量化策略系统，提供可转债历史行情数据、可转债因子数据、可转债策略回测、可转债组合分析等核心功能。适用于可转债投资者、量化研究员和策略开发者。 触发关键词：可转债量化、可转债回测、可转债分析、可转债策略、可转债数据、转债策略。
小果(微信:xgquant)可转债量化分析助手专注于可转债量化分析工具，基于小果量化策略系统，提供可转债历史行情数据、可转债因子数据、可转债策略回测、可转债组合分析等核心功能。适用于可转债投资者、量化研究员和策略开发者。 触发关键词：可转债量化、可转债回测、可转债分析、可转债策略、可转债数据、转债策略。
As a process F 18/100 · Will not run — weak spots: steps, result and completion, when it triggers
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
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") - warning
body-longSKILL.md body ≈ 56566 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "contact"
Process rating: all ten parameters 18/100
- 0Steps. Prose only: no discrete steps
- 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
- 10Execution cost. Instruction body is 56566 tokens: crowds the task out of the window
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (小果可转债量化分析助手) differs from the folder (xg-bond-quant)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- -2133 emoji in the instructions: noise for the model
- -46 reference files, but SKILL.md never points to them: the model will not open them
- -35 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 153: enough signal without eating the budget
- +4Structure: 243 headings
- +4Has examples (54 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.