AA sf-scraper
Scrape employee data from a logged-in SAP SuccessFactors browser session using browser automation. Use when: user provides an employee ID and wants employee details (name, email, department, manager, etc.) scraped directly from the SuccessFactors UI — NOT via OData/API. Requires the user to have SuccessFactors open and logged in via Chrome with the OpenClaw Browser Relay extension attached. Triggers on: "get employee name", "look up employee", "scrape SF", "find employee in SuccessFactors", or any request combining an employee ID with SuccessFactors data lookup.
As a process A 83/100 · Runs to the end — weak spots: result and completion
The same skill appears in 1 more place: ClawHub
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: 2. 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 83/100
- 0Result and completion. Does not say what the result is
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 134 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 12 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2995 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (3 tags): a typed call is more reliable
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
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 568: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 134 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.