AC platform-specs-and-validation
Platform specs and publish validation — per-platform requirements and the validate-before-publish step for multi-platform fan-out. Use when fanning a post out to multiple platforms, when a post is getting rejected, when mapping per-platform postType/required fields, or to run the validate-before-publish step. Encodes the per-platform postType enums, required-field matrices, and media rules from the OpenAPI spec, and runs POST /posts/validate so a post lands correctly on every target. Uses the CHECK framework. The keystone the per-platform format skills point to. WoopSocial validates + publishes atomically and has no update endpoint; the agent maps fields and fixes spec violations, but human-judgment calls (disclosure truthfulness, privacy intent) stay with the person; metrics never fabricated. Distinct from the per-platform format skills (one platform's content) and scheduling-and-queue (timing).
Platform specs and publish validation — per-platform requirements and the validate-before-publish step for multi-platform fan-out.
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 56/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 23 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 100Tools and files. No external tools needed
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1386 tokens
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 909: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Structure: 8 headings
- +3Step-by-step instructions: 9 items
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.