BC query-rewrite
📥 openclaw skill install dabin0927/query-rewrite —— RAG 检索命中率低？不是模型不行，是用户不会提问。 在检索前加一层 Query 改写——检测、改写、原文+改写结果都搜一遍。 6 种模式：指代消解、多意图拆解、上下文补齐、反问识别…… 实测召回率提升 60%，配合 raglite 使用效果最佳。 适合：RAG 检索前、memory_search/wiki_search 调用前。 不适合：代码生成、文件操作、单次精确查询。 (EN) RAG pre-processing query rewrite layer — 6 rewrite modes.
📥 openclaw skill install dabin0927/query-rewrite —— RAG 检索命中率低？不是模型不行，是用户不会提问。 在检索前加一层 Query 改写——检测、改写、原文+改写结果都搜一遍。 6 种模式：指代消解、多意图拆解、上下文补齐、反问识别…… 实测召回率提升…
As a process C 53/100 · 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: 4. 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 "triggers"
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. No external tools needed
- 100Steps. 17 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 937 tokens
- 100Running it twice. No mutating operations
- low 11 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
- -227 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 304: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.