CD knowledge-retrieval
A local-first document search skill with PPT/PDF support, dual-channel retrieval (keyword + AI semantic), and progressive description evolution. Designed for knowledge workers with years of local files. 给知识工作者和顾问的本地文件检索方案。支持 PPT/PDF 多格式、BM25+AI 双通道搜索、越用越聪明。适合手里有大量本地文档、不想搬上云的人。
A local-first document search skill with PPT/PDF support, dual-channel retrieval (keyword + AI semantic), and progressive description evolution.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, consistency
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: 11. 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 "skillsets" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 40Consistency. Frontmatter name (knowledge-retrieval) differs from the folder (local-knowledge-retrieval)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 29 steps, 1 vague phrases
- 100Execution cost. Instruction body is 3101 tokens
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (6 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
- -218 emoji in the instructions: noise for the model
- -31 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 277: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 29 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (5 of 7)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.