BD a-share-quant-report-reproducer
面向A股金工研报复现的 skill，自动按研报框架拆解研究问题、选择至少1000只股票的数据集、调用标准化 Python 回测框架，并按研报逻辑系统性展示结果与图片。
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ReferenceSoftware developmentData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 11. 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 39/100
- 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
- 40Consistency. Frontmatter name (a-share-quant-report-reproducer) differs from the folder (a-share-quant-report)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 140 steps
- 100Execution cost. Instruction body is 937 tokens
- low 11 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)
- +3Description length 83: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Structure: 24 headings
- +3Step-by-step instructions: 140 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.
External checks
ClawHub: clean
This skill appears to be a disclosed quant-report backtesting helper that downloads public stock data and writes local report files.
LLM: benign (high) · VirusTotal: · 29 May 2026