BD 高考志愿
提供高考志愿相关工具，获取学校和专业以往的录取分数线，提供推荐信息等。注意：往年的数据都是真实数据，当前2026年的数据还未发布，为提前获得完整体验，暂时基于2025年数据虚拟了一份，后面会及时更新。
提供高考志愿相关工具，获取学校和专业以往的录取分数线，提供推荐信息等。注意：往年的数据都是真实数据，当前2026年的数据还未发布，为提前获得完整体验，暂时基于2025年数据虚拟了一份，后面会及时更新。
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 7. 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")
Process rating: all ten parameters 49/100
- 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
- 40Consistency. Frontmatter name (高考志愿) differs from the folder (gaokao-expert-z)
- 100Tools and files. No external tools needed
- 100Steps. 14 steps
- 100Execution cost. Instruction body is 1677 tokens
- 100Running it twice. No mutating operations
- low 20 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)
- +3Description length 100: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 35 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (2 code blocks)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: clean
This skill is a disclosed admissions-advice API wrapper; its main risks are expected credential storage and sending exam-related inputs to the provider API.
LLM: benign (high) · VirusTotal: · 4 Jun 2026