BF meme-digger
网络梗考古与科普（刨根问底式）。连接贴吧（Tieba）与 B 站（Bilibili），针对用户问到的网络梗/抽象话/热梗，读取 B 站搜索、视频详情与评论区（含评论里的梗图），从评论中提取线索做发散式搜索，把 B 站、贴吧、评论、梗图、来源考证分文件收集，最后整合成一份带文字说明、梗图、来源介绍的综合科普报告。当用户问"这是什么梗 / 这个梗什么来历 / 这个说法哪来的"时使用。
网络梗考古与科普（刨根问底式）。连接贴吧（Tieba）与 B 站（Bilibili），针对用户问到的网络梗/抽象话/热梗，读取 B 站搜索、视频详情与评论区（含评论里的梗图），从评论中提取线索做发散式搜索，把 B…
As a process F 35/100 · Will not run — References files that are not bundled: images/xxx.jpg, images/yyy.jpg, scripts/...
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: 14. 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") - warning
missing-refreference to a missing file: images/xxx.jpg - warning
missing-refreference to a missing file: images/yyy.jpg - warning
missing-refreference to a missing file: scripts/... - warning
missing-refreference to a missing file: templates/encyclopedia.css
Process rating: all ten parameters 35/100
- 0Tools and files. 4 referenced file(s) missing: images/xxx.jpg, images/yyy.jpg, scripts/...
- 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
- 100Steps. 64 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1718 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
- +2Single-language instructions
- +3Description length 191: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 64 items
- +4Has examples (9 code blocks)
- +3All 10 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.