AD rstack
The operator skill suite for the agentic web. Helps resolved.sh operators maximize their presence and build a successful agent-native business: audit page quality, craft A2A agent cards, optimize data products, register paid service endpoints, publish monetized content (blog posts, courses, paywalled sections), and distribute to Smithery, mcp.so, skills.sh, and other registries. Start with /rstack-audit to get a scorecard, then run the skills it recommends. Use when asked to "audit my resolved.sh page", "improve my agent presence", "sell API calls", "publish a course", "get discovered", or "optimize my data listing".
As a process D 39/100 · Unfinished process — 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: 3. 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 39/100
- 0Result and completion. Does not say what the result is
- 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. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (rstack) differs from the folder (resolved-sh-rstack)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 10 steps
- 100Execution cost. Instruction body is 303 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 624: enough signal without eating the budget
- +4Structure: 3 headings
- +3Step-by-step instructions: 10 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.