AD football-predict
足球赛事预测神器。自动采集 titan007.com 数据（亚盘、大小球、欧赔、基本面、阵容、角球、半全场）， 5 步量化分析框架，输出投注建议与预测比分。Football match betting prediction system. Auto-scrapes data from m.nowscore.com (Asian handicap, over/under, European odds, fundamentals, lineups, corners, half-time goals), runs a 5-step quantitative analysis framework, and outputs betting recommendations with predicted scores. Supports concise/visual dual output modes, post-match review, and auto weight optimization. Triggers: (1) match ID like "2908467" or match description, (2) requests to predict/analyze football matches (e.g. "predict", "analyze this match"), (3) match results for post-match review (e.g. "review", "result was 2-1"), (4) handicap/over-under analysis.
As a process D 49/100 · Unfinished process — 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: 6. 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 49/100
- 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
- 40Consistency. Frontmatter name (football-predict) differs from the folder (ballball)
- 100Tools and files. No external tools needed
- 100Steps. 33 steps
- 100Execution cost. Instruction body is 482 tokens
- 100Running it twice. No mutating operations
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 707: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 33 items
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.