CF custom-asset-manager
管理自建图库(角色库、道具库、场景库)全生命周期资产。支持初始化与挂载图库目录、新增归档资产、替换基准图、修改名称与标签、安全删除资产、查询清单及自动刷新画廊。当用户提出“添加到角色库”、“替换IP图片”、“修改角色名称”、“删除角色/道具/场景”、“初始化图库目录”等资产维护需求时使用。
管理自建图库(角色库、道具库、场景库)全生命周期资产。支持初始化与挂载图库目录、新增归档资产、替换基准图、修改名称与标签、安全删除资产、查询清单及自动刷新画廊。当用户提出“添加到角色库”、“替换IP图片”、“修改角色名称”、“删除角色/道具/场景”、“初始化图库目录”等资产维护需求时使用。
As a process F 33/100 · No process to follow — References files that are not bundled: ../handdraw-style-prompter/scripts/custom_library_manager.py
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: 1. 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: ../handdraw-style-prompter/scripts/custom_library_manager.py
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: ../handdraw-style-prompter/scripts/custom_library_manager.py
- 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
- 30Running it twice. 3 mutating operations with no state check
- 100Steps. 53 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 757 tokens
- low The response is described with custom markup (5 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 145: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 53 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.