BC kickbacks
Kickbacks.ai — an executable guide to earning passive income from AI tool waiting time. Covers 7 use cases: ① Getting Started — ("How to install Kickbacks" "How to earn money with Claude Code" "How does Kickbacks work") ② Understanding the Economics — ("How much can I earn" "How are ads priced" "What is 50% revenue share") ③ Advertiser Tools — ("How to advertise on Kickbacks" "How to bid on the spinner" "How much does an ad cost") ④ Troubleshooting — ("Kickbacks not working" "Extension not showing" "Status bar says incompatible") ⑤ Analytics & Earnings — ("How to check my balance" "How do payouts work" "How many impressions did I get") ⑥ Privacy & Security — ("Is Kickbacks safe" "Does it read my code" "Is it reversible") ⑦ OpenClaw/Hermes Adapter — ("How to use Kickbacks with OpenClaw" "Can I run ads on other agent platforms" "How to become the default advertiser") Trigger when users say: "Kickbacks" "Get paid for waiting" "Claude Code ads" "spinner money" "earn while coding" "Kickbacks.ai" "Discombobulating" "codex ads" "paid spinner" "spinner advertising platform" "OpenClaw ads" "agent platform monetization" "default advertiser" or mention: kickbacks / spinner / Claude Code monetize / Codex passive income / IDE extension / OpenClaw monetization / Hermes ads / agent waiting time.
Kickbacks.ai — an executable guide to earning passive income from AI tool waiting time. Covers 7 use cases: ① Getting Started — ("How to install Kickbacks"…
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
How to improve
- Shorten the description to 1024 characters.
- 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: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1301 chars, limit 1024
Process rating: all ten parameters 58/100
- 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
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 70When it triggers. States when to use, but not when not to
- 100Steps. 45 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2065 tokens
- 100Running it twice. Mutating operations check current state
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1301: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -214 emoji in the instructions: noise for the model
- +2Single-language instructions
- +5Description quotes 34 example trigger phrases
- +4Structure: 10 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.