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AI广告投手全流程助手。覆盖数据导入→投放分析→预算优化→素材诊断→智能报表→异常告警6大阶段。支持多平台(腾讯广告/巨量引擎/百度推广/Meta/Google Ads)数据统一分析,自动生成交互式HTML可视化报告,提供ROI/ROAS/CTR/CVR/CPA等多维度智能诊断和优化建议。触发词:广告投手, 投放分析, 广告优化, ROI分析, 素材分析, 广告报表, 投放诊断, 预算优化, 广告数据, ad trader, 投手报告, 广告账户诊断, 转化分析, 广告素材诊断, 广告出价优化。

ClawHub Agent Skills author: bettermen v1.0.0 MIT-0 12 files body ≈ 523 tokens Open the sourceclawhub.ai analyzed 2 d ago

AI广告投手全流程助手。覆盖数据导入→投放分析→预算优化→素材诊断→智能报表→异常告警6大阶段。支持多平台(腾讯广告/巨量引擎/百度推广/Meta/Google Ads)数据统一分析,自动生成交互式HTML可视化报告,提供ROI/ROAS/CTR/CVR/CPA等多维度智能诊断和优化建议。触发词:广告投手…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMarketingData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 12. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 24 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 523 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (5 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
  • +2Single-language instructions
  • +3Description length 250: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 5 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This skill is a coherent advertising-data analysis and reporting helper, with manageable risks around broad invocation wording and CDN-based report charts.
LLM: benign (high) · VirusTotal: · 21 Jun 2026