AC iphone-malware-scan
End-to-end iOS malware/spyware forensic assessment of a non-jailbroken iPhone from a Mac. Installs tooling (libimobiledevice + Mobile Verification Toolkit), pulls crash logs, creates a full ENCRYPTED device backup (auto-resuming on lock/disconnect), decrypts it, runs MVT against every spyware IOC feed (Pegasus, Predator, Candiru, Cellebrite, Intellexa, stalkerware, ...), sweeps every file in the backup manifest, analyzes crash logs for injected dylibs, and produces an assessment report. Use when the user suspects their iPhone is compromised, asks to check for spyware/Pegasus/stalkerware, or wants a full forensic health check of an iPhone connected over USB.
End-to-end iOS malware/spyware forensic assessment of a non-jailbroken iPhone from a Mac.
As a process C 64/100 · Has gaps — weak spots: result and completion, 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: 11. 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 64/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 924 tokens
- 100Progress reporting. Reports progress
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
- -31 of 9 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 665: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.