AC free-model-auditor
审计 WorkBuddy 自定义模型注册表（models.json）中的免费模型：跨多个 OpenAI 兼容厂商新增可发现的免费模型、 剔除已转付费或失效的模型，保持注册表真实有效。当用户要求「审计自定义模型」「检查有没有新的免费模型」 「测试其余平台有无遗漏」「定期巡检模型清单」或希望对免费 API 模型做健康检查时使用。 本技能对海外平台执行 VPN 连通性门禁，按各厂商策略判定免费，活体实测每个候选，并自动把新增/移除差异应用到 models.json。
审计 WorkBuddy 自定义模型注册表（models.json）中的免费模型：跨多个 OpenAI 兼容厂商新增可发现的免费模型、 剔除已转付费或失效的模型，保持注册表真实有效。当用户要求「审计自定义模型」「检查有没有新的免费模型」 「测试其余平台有无遗漏」「定期巡检模型清单」或希望对免费 API…
As a process C 51/100 · Has gaps — 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.
- 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: 8. 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") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 51/100
- 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
- 30Running it twice. 6 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 47 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1900 tokens
- low The response is described with custom markup (4 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
- +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 232: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.