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Plan, execute, and optimize paid ad campaigns across Google, Meta, LinkedIn, Twitter/X, and TikTok, covering targeting, budget, bid strategies, and retargeting. Use when running PPC campaigns, setting up ad accounts, or optimizing ROAS/CPA.

borghei/Claude-Skills Agent Skills author: borghei 4 files · 3 scripts body ≈ 6 781 tokens Open the sourcegithub.com↗ analyzed 8 h ago

Plan, execute, and optimize paid ad campaigns across Google, Meta, LinkedIn, Twitter/X, and TikTok, covering targeting, budget, bid strategies, and retargeting.

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureYouTubeMarketingtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
96
Quality 40%
78
Run on models
none yet
Process rating
C
61/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Secrets in code secret-high-entropy-token SKILL.md:142
    High-entropy token-like string (may be an id, hash or a credential)
    GOOG…6Q1
  • low Secrets in code secret-high-entropy-token SKILL.md:143
    High-entropy token-like string (may be an id, hash or a credential)
    META…r26
  • low Secrets in code secret-high-entropy-token SKILL.md:144
    High-entropy token-like string (may be an id, hash or a credential)
    LI_L…6Q1
  • low Secrets in code secret-high-entropy-token SKILL.md:145
    High-entropy token-like string (may be an id, hash or a credential)
    TIKT…r26

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6781 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 61/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6781 tokens
  • 100Steps. 112 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 20 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
  • +2Single-language instructions
  • +3Description length 240: enough signal without eating the budget
  • +4Structure: 53 headings
  • +3Step-by-step instructions: 112 items
  • +4Has examples (8 code blocks)
  • +3All 3 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.