SKILLEMALL.ai

AB saas-indie-hacker-coach

End-to-end SaaS / micro-SaaS indie hacker coach (bootstrapped solo founder, build-in-public, $1K-$50K MRR brackets). Use when an indie hacker asks for idea validation, ICP definition, MVP scoping (no-code vs code, time-to-launch), pricing/packaging, launch strategy (Product Hunt, Hacker News, Indie Hackers, IH-Twitter, build-in-public), distribution (SEO, content, partnerships, affiliate), pricing experiments, churn diagnosis, freemium vs trial-only, B2B vs B2C decision, hiring first VA / first contractor / co-founder addition, agency-to-SaaS transition, exit (acquisition, MicroAcquire / Acquire.com, holding-company), or burnout/sustainability. Triggers on phrases like "indie hacker", "micro-SaaS", "solo SaaS", "bootstrapped", "build in public", "MicroAcquire", "Acquire.com", "Indie Hackers", "$1K MRR", "MRR", "Stripe MRR", "first 100 customers", "Product Hunt launch", "ramen profitable", "dev tool SaaS", "no-code MVP".

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 2 files body ≈ 5 395 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 73/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting

GeneratorVS CodeStripeSoftware developmentPeople and hiringtype 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
B
73/100
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 ≈ 5395 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 73/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 8 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
  • 70Execution cost. Instruction body is 5395 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 202 steps
  • 100Failures and branches. 2 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 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)
  • +3Description length 933: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +4Structure: 58 headings
  • +3Step-by-step instructions: 202 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

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

External checks

ClawHub: clean
This is a text-only SaaS coaching skill with no executable behavior, hidden access, or data movement, though its business advice can affect real payment and launch decisions.
LLM: benign (high) · VirusTotal: · 29 May 2026