BD ai-cost-cutter
当用户说『API账单太贵』『token烧太快』『能不能用本地模型』『批处理怎么省钱』『离线跑AI』，或要把大模型调用从烧钱变省钱时使用。四把刀降本：批处理（高峰调度/合并请求）、本地模型回退（贱活本地跑、贵活才上云）、缓存层（相同请求不重复花钱）、模型路由分级（按任务难度选便宜/贵模型）。附可运行成本估算脚本，输入任务量+模型单价即输出月度账单与三档降本方案的差额。源自 GOSIM 参赛作 cross-machine-offline-taskbox 的离线跑批思路。触发词：AI省钱、降本、token太贵、本地模型、批处理、离线跑AI、模型路由、缓存层、cost cutter、AI成本、API账单。
当用户说『API账单太贵』『token烧太快』『能不能用本地模型』『批处理怎么省钱』『离线跑AI』，或要把大模型调用从烧钱变省钱时使用。四把刀降本：批处理（高峰调度/合并请求）、本地模型回退（贱活本地跑、贵活才上云）、缓存层（相同请求不重复花钱）、模型路由分级（按任务难度选便宜/贵模型）。附可运行成本估算脚本，输入任…
As a process D 46/100 · 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 Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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
description-long-hermesdescription is 302 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "title" - note
frontmatter-keyunknown frontmatter key "display_name_en" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "copyright" - note
frontmatter-keyunknown frontmatter key "read_when" - note
frontmatter-keyunknown frontmatter key "homepage"
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
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 10 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 502 tokens
- 100Running it twice. No mutating operations
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
- -31 of 1 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 302: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.