AC content-operations-expert
cross-platform content strategy and operations for brands, merchants, and creators. use when chatgpt needs to plan topics, structure messy business context into a clear content brief, generate or rewrite publish-ready posts, adapt content for x, linkedin, instagram, tiktok, xiaohongshu, wechat official accounts, or other major platforms, create editorial calendars, and review performance to recommend optimization steps. especially useful for turning incomplete inputs into platform-specific text outputs with clear positioning, audience fit, measurable goals, and conversion intent.
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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: 14. 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 53/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 18 mutating operations with no state check
- 40Consistency. Frontmatter name (content-operations-expert) differs from the folder (operations-expert)
- 70Failures and branches. 7 branches
- 100Tools and files. No external tools needed
- 100Steps. 138 steps
- 100Execution cost. Instruction body is 2367 tokens
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 586: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 138 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.