BD 佛学讲评助手
佛教讲说/复讲/授课/演讲的自动评测与评分工具（通用版）。上传音频或视频（不支持纯文字稿），自动转写→双轨评估（讲说风格+内容分类）→六维打分（教义准确/结构逻辑/语言表达/契机应变/感悟感染/自主发挥）→生成图表化 HTML 报告。含结构大纲（简短 inline、较长换行）、来源比对（L0 大藏经+L1 天台藏+关键断言核验，去数字 ID，附 CBETA 行级深链）、读稿检测、音频-文本对齐分析、★讲述性质识别（仅在有实锤时显示复讲判定模块；v2.26 增强来源核验行级深链，v2.25 增强收尾自陈复讲/复述识别与卡顿/重复特征）、★复讲/副讲独立量表（与原创讲授解耦，前台仅展示判定依据/加分项/减分项/说明四项；后台增强开场结尾仪式提取、念诵溯源、卡顿与前后重复密度）。输出配色与版式已固化，跨平台（WorkBuddy/IMA/其他大模型）渲染一致。触发词：讲经评测、讲评分析、佛教演讲评分、复讲评价、授课评估、佛学讲说打分。
佛教讲说/复讲/授课/演讲的自动评测与评分工具（通用版）。上传音频或视频（不支持纯文字稿），自动转写→双轨评估（讲说风格+内容分类）→六维打分（教义准确/结构逻辑/语言表达/契机应变/感悟感染/自主发挥）→生成图表化 HTML 报告。含结构大纲（简短 inline、较长换行）、来源比对（L0 大藏经+L1…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 1
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high Dangerous commands
cmd-install-from-urlSKILL.md:45Installs a package from an untrusted URL / archivepip install -i https://pypi.tuna.tsinghua.edu.cn/simple faster-whisper soundfile
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- 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") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "type" - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 46/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (佛学讲评助手) differs from the folder (sikll)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 106 steps
- 100Execution cost. Instruction body is 3266 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
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 419: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 106 items
- +4Has examples (7 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.