SKILLEMALL.ai

AB podcast-monetization-coach

End-to-end podcast monetization & growth coach. Use when a podcaster asks for sponsorship strategy (host-read, programmatic, dynamic-insertion), CPM pricing, media-kit structure, sponsor-pitching outreach, audience-growth tactics, premium / paid feed (Patreon, Apple Subscriptions, Supercast, Memberful), affiliate-stack design, ad-network selection (Megaphone, Acast, Spotify Audience Network, Spreaker), live-event monetization, course/coaching upsell from podcast, branded-podcast services for B2B, or exit/sale. Triggers on phrases like "podcast sponsorship", "host-read ad", "CPM", "podcast network", "Patreon for podcast", "premium podcast feed", "Apple Subscriptions", "Supercast", "podcast media kit", "sponsor outreach", "podcast monetize", "branded podcast".

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 2 files body ≈ 5 148 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

ReferenceMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
B
70/100
Nearly there
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 · 0

✓ No critical or high findings

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5148 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 70/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 11 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Failures and branches. 4 branches
  • 70Execution cost. Instruction body is 5148 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 148 steps
  • 100Consistency. Name and required fields are in place
  • low 15 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 11 example trigger phrases
  • +3Description length 768: enough signal without eating the budget
  • +4Structure: 46 headings
  • +3Step-by-step instructions: 148 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

External checks

ClawHub: clean
This is a text-only podcast business coaching skill with no executable behavior, persistence, or hidden data access.
LLM: benign (high) · VirusTotal: · 29 May 2026