SKILLEMALL.ai
GitHub ↗ RU Sign in

BD meta-ads-daily-pulse

[Didoo AI] Rapid daily health scan for Meta Ads — detects week-over-week performance changes and flags urgent issues before meetings. Use every morning or before any daily review meeting. This is a change detector, not a full diagnostic.

ClawHub Agent Skills author: Elias@Didoo v1.1.0 MIT-0 2 files body ≈ 1 253 tokens Open the sourceclawhub.ai↗ analyzed 11 d ago

[Didoo AI] Rapid daily health scan for Meta Ads — detects week-over-week performance changes and flags urgent issues before meetings.

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches

AnalyzerMarketingtype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 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. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 18 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1253 tokens

    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 237: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: suspicious
    This Meta Ads monitoring skill is coherent, but it needs review because its example API calls place the access token in the URL where it may leak through logs or diagnostics.
    LLM: suspicious (high) · VirusTotal: · 16 Sept 2026