BF Chanlun Technical Analysis Expert
AI-powered Chanlun (Zen Trading) technical analysis skill based on the complete "Teach You to Trade Stocks 108 Lessons" (缠中说禅108课) original theory. Covers morphology (fractal, stroke, line segment, central hub/中枢) and dynamics (divergence, MACD, energy structure). Updated 2026 with chan.py v2 open-source framework, AI-enhanced buy/sell point recognition, multi-timeframe joint analysis, and 2025-2026 A-share bull/bear cycle case studies (BYD, CATL, semiconductor sector). Keywords: Chanlun, technical analysis, A-share, chan.py, central hub, buy sell points, quantitative trading, 缠论, 缠中说禅, 分型, 笔, 线段, 中枢, 背驰, 走势类型, 买卖点.
As a process F 28/100 · Will not run — References files that are not bundled: references/chanlun_case_studies.md, references/chanlun_algorithm_python.md, references/chanlun_practice_guide.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 2. 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 3, column 14: description: AI-powered Chanlun (Zen Trading) technical analysis skill based on… ^ ); 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) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: references/chanlun_case_studies.md - warning
missing-refreference to a missing file: references/chanlun_algorithm_python.md - warning
missing-refreference to a missing file: references/chanlun_practice_guide.md - warning
missing-refreference to a missing file: references/chanlun_analysis_templates.md - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 28/100
- 0Tools and files. 4 referenced file(s) missing: references/chanlun_case_studies.md, references/chanlun_algorithm_python.md, references/chanlun_practice_guide.md
- 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. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (Chanlun Technical Analysis Expert) differs from the folder (chanlun-analysis-pro)
- 100Steps. 33 steps
- 100Execution cost. Instruction body is 3274 tokens
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 623: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (16 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 44.