BD tencentcloud-ocr-multimodaldocparse
腾讯云多模态解析（文档版）(MultimodalDocParse) 技能包。当用户提供文档 URL 地址时，应自动调用多模态解析（文档版）接口提取文档内容信息。支持 PDF、Word、PPT、Excel、Markdown、TXT、图片、WPS 等多格式文档解析；可配置页码范围、子图解析、任务类型、输出格式等可选参数；接口返回 ZIP 格式结果包下载地址，包内含结构化解析结果（*.md / *.xml / *_ocr_page{N}.json）及文档内提取的图片素材（images/）。结果包的真实结构与字段说明详见 references/result-package-structure.md。
腾讯云多模态解析（文档版）(MultimodalDocParse) 技能包。当用户提供文档 URL 地址时，应自动调用多模态解析（文档版）接口提取文档内容信息。支持 PDF、Word、PPT、Excel、Markdown、TXT、图片、WPS…
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Dangerous commands
cmd-shell-rcSKILL.md:238Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_ID="你的SecretId"' >> ~/.bashrc
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medium Dangerous commands
cmd-shell-rcSKILL.md:239Writes to a shell startup fileecho 'export TENCENTCLOUD_SECRET_KEY="你的SecretKey"' >> ~/.bashrc
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")
Process rating: all ten parameters 41/100
- 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
- 40Consistency. Frontmatter name (tencentcloud-ocr-multimodaldocparse) differs from the folder (tencentcloud-multimodaldocparse-ocr)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 40 steps
- 100Execution cost. Instruction body is 2068 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
- -214 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 299: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 40 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.