AC social-seo
Use to make social content discoverable through SEARCH across social platforms — the social-SEO / keyword-discovery skill. Run when the user says "social SEO," "get found in search," "TikTok SEO," "YouTube SEO," "keywords for social," "searchable captions," or wants search across platforms rather than just the feed. For single-platform depth, route "Instagram SEO" to instagram-seo and Pinterest asks to pinterest-seo; this skill owns the cross-platform framework. Reads brand-profile and audience first. All platforms are search engines; keywords, not hashtags, are the lever. Covers per-platform indexed surfaces, keyword research via autocomplete + native analytics (never fabricates volumes), the triple-mention technique, topical clusters, and the profile as a search asset. Routes hashtags to hashtag-strategy; hands the AI-search/LLM-citation (GEO) layer to ai-search-optimization. Measures via native search insights, not WoopSocial analytics.
Use to make social content discoverable through SEARCH across social platforms — the social-SEO / keyword-discovery skill.
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: 1. 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. 3 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. 33 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1741 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 953: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +4Structure: 13 headings
- +3Step-by-step instructions: 33 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.