BF generating-evaluation-rubrics
Generate structured evaluation rubrics (评价量规/评估量表) from teaching plan (教案) content. Supports text input, pasted content, and file uploads (PDF/Word/Markdown). Covers primary, secondary, and vocational education across subjects. Outputs styled Excel with star ratings (过程) and scored criteria (结果). Use when: (1) user provides lesson plan content or teaching design and requests evaluation criteria, scoring standards, or assessment framework; (2) user mentions evaluation rubric keywords: 评价量规, 评估量表, 教学评价表, 课堂评价, 学习评价, 量规表, 教案评估, 课堂教学评价, rubric, assessment table; (3) user uploads teaching documents and asks for a structured classroom assessment table.
Generate structured evaluation rubrics (评价量规/评估量表) from teaching plan (教案) content.
As a process F 35/100 · Will not run — References files that are not bundled: scripts/generate_rubric.py, references/examples.md
How to improve
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Generate structured evaluation rubrics (评价量规/评估量表) from teaching p… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: scripts/generate_rubric.py - warning
missing-refreference to a missing file: references/examples.md
Process rating: all ten parameters 35/100
- 0Tools and files. 2 referenced file(s) missing: scripts/generate_rubric.py, references/examples.md
- 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. 66 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1438 tokens
- 100Running it twice. No mutating operations
- low 12 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
- +1No license
- +2Single-language instructions
- +3Description length 654: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 66 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.