AC context-compressor-pro
上下文压缩器专业版是Agent记忆管控的完整压缩方案。在免费版基础上解锁成批压缩自发化、智能分类归档（决策/教训/待办/事实/偏好五类）、增量压缩（仅处置新增内容）、压缩质量评分（信息保留率量化评估）、自定义输出模板、压缩历史追踪、多语言混合日志调优七大高级功能。Use when 需要文本翻译、多语言转换、本地化处理时使用。不适用于专业医学法律翻译认证。
上下文压缩器专业版是Agent记忆管控的完整压缩方案。在免费版基础上解锁成批压缩自发化、智能分类归档（决策/教训/待办/事实/偏好五类）、增量压缩（仅处置新增内容）、压缩质量评分（信息保留率量化评估）、自定义输出模板、压缩历史追踪、多语言混合日志调优七大高级功能。Use when…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 178 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "tools" - note
frontmatter-keyunknown frontmatter key "pricing_tier"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 55 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3690 tokens
- 100Running it twice. No mutating operations
- low 18 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
- +2Single-language instructions
- +3Description length 178: enough signal without eating the budget
- +4Structure: 58 headings
- +3Step-by-step instructions: 55 items
- +4Has examples (20 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.