AC b2c-organic-social-media-marketing
Organic growth coach for B2C apps and products on TikTok and Instagram, with no ad spend. Covers account creation, the 7-day warmup before posting, finding content-market fit, hook and caption formulas, CTA placement, riding trends, converting views into downloads, and when to scale to multiple accounts and automate with Post Bridge.
Organic growth coach for B2C apps and products on TikTok and Instagram, with no ad spend.
As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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-keyunknown frontmatter key "last-updated"
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 5 mutating operations with no state check
- 40Consistency. Frontmatter name (b2c-organic-social-media-marketing) differs from the folder (b2c-marketing)
- 70When it triggers. States when to use, but not when not to
- 85Steps. 76 steps, 2 vague phrases
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 3208 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 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
- +1No license
- +2Single-language instructions
- +3Description length 335: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 76 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.