BF sports-data-analysis
一句话生成今日赛事全景报告 · 覆盖足球/篮球/NBA/英超/中超/欧冠等13类运动，阵型动画+球员聚焦+数据雷达，把"今天有啥比赛、谁上场、怎么打"一眼看全。不做赛果判断、只做信息整理与可视化，主动打假收费荐单话术。球迷看球、解说备稿、体育教学都能用。
一句话生成今日赛事全景报告 · 覆盖足球/篮球/NBA/英超/中超/欧冠等13类运动，阵型动画+球员聚焦+数据雷达，把"今天有啥比赛、谁上场、怎么打"一眼看全。不做赛果判断、只做信息整理与可视化，主动打假收费荐单话术。球迷看球、解说备稿、体育教学都能用。
As a process F 31/100 · Will not run — References files that are not bundled: assets/cover.svg, assets/icon.svg
This is a copy of a skill from another catalog; the rating counts the canonical one: sports-data-analysis (ClawHub)
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The text references files that are not there: add them or drop the references.
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: 21. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 127 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - warning
missing-refreference to a missing file: assets/cover.svg - warning
missing-refreference to a missing file: assets/icon.svg - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 31/100
Will not run. References files that are not bundled: assets/cover.svg, assets/icon.svg
- 0Tools and files. 2 referenced file(s) missing: assets/cover.svg, assets/icon.svg
- 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 (sports-data-analysis) differs from the folder (sport-skill)
- 100Steps. 74 steps
- 100Execution cost. Instruction body is 3272 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (6 tags): a typed call is more reliable
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
- -240 emoji in the instructions: noise for the model
- -31 of 6 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 127: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 7)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.
External checks
ClawHub: suspicious
This sports-reporting skill is broadly coherent, but it asks for automatic execution, broad web fetching, local file mutation, and persistent/report writes with weaker scoping than users should accept without review.
LLM: suspicious (high) · 27 Aug 2026