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AC baidu-milan-winter-olympics-2026

获取2026年米兰冬奥会数据技能，包括奖牌榜排名、现场新闻报道和赛程安排。从百度体育网页抓取实时的奖牌排行榜信息、最新新闻资讯和比赛赛程。当用户需要获取米兰冬奥会需求，需要查询冬奥会奖牌榜、了解各国奖牌数量、获取现场新闻、查看赛程安排时使用此技能。能够根据指定时间(今天、明天、yyyy-MM-dd日期格式)或指定运动项目获取赛程安排。A skill for retrieving 2026 Milan Winter Olympics data, including medal standings, live news reports, and competition schedules. Scrapes real-time medal rankings, latest news, and match schedules from Baidu Sports. Use this skill when users need to query Winter Olympics medal standings, check medal counts by country, get live news, or view competition schedules.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 1 421 tokens Open the sourcegithub.com↗ analyzed 2 d ago

获取2026年米兰冬奥会数据技能，包括奖牌榜排名、现场新闻报道和赛程安排。从百度体育网页抓取实时的奖牌排行榜信息、最新新闻资讯和比赛赛程。当用户需要获取米兰冬奥会需求，需要查询冬奥会奖牌榜、了解各国奖牌数量、获取现场新闻、查看赛程安排时使用此技能。能够根据指定时间(今天、明天、yyyy-MM-dd日期格式)或指定运动…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 41 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1421 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

    • +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 532: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 41 items
    • +4Has examples (25 code blocks)
    • +3All 4 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.