BF yotta-present
元呈 —— AI 输出的默认呈现层：智能体先把输出内容判为「内容类型」，再选「呈现形态」（结论卡/表格/正文/指标板/问答卡/报告/图表…），用 yotta_present CLI 或 present_result MCP 统一渲染成可复制的 Markdown / 纯文本（按需附本地 SVG）。平台自适应（--platform / platform）：webchat 完整 Markdown、discord/whatsapp 表格转列表+标题转加粗、plain 去符号；渲染通道（--channel / channel）：auto 按 platform 映射 plain→r0 去 emoji、其余→r1 emoji 徽章+引用条（r0 保底无色 / r1 增强，r2/r3 高级美化未开放）；命名场景模板（vuln_report/faq/status，references/templates.json 可热更新）一次定义多处复用；codeblock + bold_keys 加粗 + max_len 长度熔断。触发：默认——凡交付给用户的 AI 输出都经元呈（判型 → 选形态 → 渲染）呈现；例外见正文白名单。边界：不做交互式图表编辑器 / BI / 数据分析工具；图表只是呈现形态之一；不做内容改写 / 判断本身。AI 首次使用自动接入 yotta-present MCP（写 mcpServers + 永久记忆护栏，均需用户明确同意），输出默认统一呈现、未加载时降级 CLI。
元呈 —— AI 输出的默认呈现层：智能体先把输出内容判为「内容类型」，再选「呈现形态」（结论卡/表格/正文/指标板/问答卡/报告/图表…），用 yottapresent CLI 或 presentresult MCP 统一渲染成可复制的 Markdown / 纯文本（按需附本地…
As a process F 38/100 · Will not run — References files that are not bundled: scripts/yotta_humanize.py
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 18. 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") - warning
missing-refreference to a missing file: scripts/yotta_humanize.py
Process rating: all ten parameters 38/100
- 0Tools and files. 1 referenced file(s) missing: scripts/yotta_humanize.py
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 58 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2446 tokens
- low 10 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
- -32 of 5 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 644: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 58 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.