BF delonix-intelligence-suite-v2
德胧AI龙虾军团舆情情报综合工具箱 v2.0。整合 miaoda搜索 + BettaFish开源舆情引擎 + 飞书精美卡片 + 抖音/视频平台监控 + AI风险分析与防控预案生成。 触发词：舆情、情报、网情、监控、风险分析、抖音监控、酒店风险、德胧舆情、竞品动态、行业预警 三大核心能力： 1. 外网信息采集（miaoda搜索主力 + BettaFish扩展） 2. 精美飞书卡片输出（可视化日报） 3. AI风险分析+防控预案（舆情驱动决策）
As a process F 35/100 · Will not run — References files that are not bundled: url
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.
For the model run — optional
- 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: 3. 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: url - note
frontmatter-keyunknown frontmatter key "override-tools"
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: url
- 0Tools and files. 1 referenced file(s) missing: url
- 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
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2046 tokens
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 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
- -215 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 224: enough signal without eating the budget
- +4Structure: 45 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (17 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.
External checks
ClawHub: suspicious
This is a coherent public-opinion monitoring skill, but it needs review because it includes broad activation terms, recurring monitoring examples, and outbound Feishu reporting without enough scoping controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026