BD aios-make-chart-image
当 OpenClaw 或 AIOS agent 需要把 JSON、Markdown 表格或 ECharts option 渲染成图表图片时,必须使用本技能。使用内置 JavaScript 脚本解析数据、生成 ECharts 配置,并导出 PNG、SVG、JPEG 或 WebP 图片;不要临时手写浏览器截图流程。
当 OpenClaw 或 AIOS agent 需要把 JSON、Markdown 表格或 ECharts option 渲染成图表图片时,必须使用本技能。使用内置 JavaScript 脚本解析数据、生成 ECharts 配置,并导出 PNG、SVG、JPEG 或 WebP 图片;不要临时手写浏览器截图流程。
As a process D 43/100 · 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.
- 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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:18High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…U5f+Jr/W5tZ…4rk/SNOQiFWmaR/VKF4…6Pg==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:120High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…byA+l3XtsAj+Q8tf…oOo+X6HZ…Q8A==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:177High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…bSm+x6ETixtKZBh/qbRE…8Sr/Wcyx…yGA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:234High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…UzJ+En8KcVm9Lk5+uGUQ…GXw==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:272High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…595+ujv0…pwV/GONa…zQo/1O6zRIkh0m/8+5Bjr…SZw==",
detector
Files scanned: 6. 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 43/100
- 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
- 30Running it twice. 12 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 768 tokens
- 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
- +1No license
- +2Single-language instructions
- +3Description length 156: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (5 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.