AC linkedin-page-publisher
Publish posts programmatically to a LinkedIn Company Page via the versioned Posts API (/rest/posts), including text posts, single-image posts, multi-image carousels, video posts, and article link previews. Handles the full multi-step media upload flow (initializeUpload → PUT binary → wait for LinkedIn to finish processing → reference URN in the post). Use this skill whenever the user wants to post to LinkedIn, publish to a Company Page, automate LinkedIn content, cross-post to LinkedIn from another system, build a LinkedIn publishing bot or scheduler, or upload images or videos to LinkedIn programmatically — even when they don't say "API" explicitly. Also use it when the user mentions errors from the LinkedIn Posts API, w_organization_social scope, urn:li:organization URNs, UGC posts, or /rest/images and /rest/videos endpoints.
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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: 10. 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 59/100
- 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. 10 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 20 steps
- 100Failures and branches. 5 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1915 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)
- +3Description length 839: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 14 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.