AC instagram-growth
Use to grow an Instagram account — the Instagram-specific growth strategy that diagnoses where growth is stuck (reach, follow-conversion, retention, or shares) and orchestrates the other skills to fix it. Run when the user says "grow on Instagram," "Instagram growth," "get more followers/reach on Instagram," "my Instagram isn't growing," "Instagram strategy," or wants more reach/followers on IG. Reads brand-profile, social-strategy, and audience first. Built on the 2026 reality that Instagram is a discovery engine where watch time and sends (DM shares) drive non-follower reach. Diagnoses the broken stage of the growth loop and routes to the right skill (reels-script, carousel-writer, profile-optimization, content-calendar, hashtag-strategy, trend-jacking). Judges via native Instagram Insights — not WoopSocial analytics — and treats follower count as vanity.
Use to grow an Instagram account — the Instagram-specific growth strategy that diagnoses where growth is stuck (reach, follow-conversion, retention, or…
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 62/100
- 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
- 30Running it twice. 19 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1500 tokens
- low 12 top-level sections: this looks like several domains in one skill
- low No test case covers injection arriving through data
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 869: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +4Structure: 13 headings
- +3Step-by-step instructions: 30 items
- +4Reference files are cited in the instructions (4 of 4)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.