Screencap vs SkillSpector: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Screencap and SkillSpector — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Screencap
Proteus Computer Use
Local-first macOS screen recorder that captures, labels, and indexes team workflows so knowledge stays searchable and private.
Key features
- Local-First Capture: Recordings live in ~/.screencap on your Mac and never leave unless you explicitly share them.
- On-Device Task Segmentation: An on-device model breaks long recordings into labeled tasks like payroll runs, expense approvals, or CRM data entry.
- Full-Text Search of Workflows: Every spoken word and on-screen moment is indexed so any past workflow can be surfaced months later by search.
- Privacy-Enforced Recording: Password managers and banking apps are cut before a frame is written; email and chat are masked in real time.
- MCP Context Snapshots: While recording, Screencap queries connected MCP servers to capture the exact Gusto/Attio/Linear/Notion record on screen inside the video.
- Deliberate Sharing With PII Scrubbing: Every shared copy is scrubbed of names, secrets, and PII, and only the recordings you pick ever leave the machine.
- Source-Available Codebase: The full capture engine, encryption, agent, and anonymizer are public on GitHub under PolyForm Noncommercial 1.0.0.
Best for
- Team Onboarding: Assemble ordered collections of real workflow recordings so new teammates learn exactly how work is actually done.
- Institutional Knowledge Capture: Preserve the tacit steps behind payroll runs, reconciliations, and quarterly reports as searchable video.
- Ops Documentation: Replace stale wikis by pointing teammates at labeled task recordings that stay current with the real system.
- Compliance-Sensitive Recording: Capture back-office work in banking, finance, and HR without leaking passwords, account balances, or PII.
- Computer-Use Dataset Contribution: Optionally donate reviewed, scrubbed recordings to a public dataset for training open computer-use models.
S
SkillSpector
NVIDIA
SkillSpector is NVIDIA's open-source security scanner that detects vulnerabilities, malicious patterns, and policy risks in AI agent skills.
Key features
- Vulnerability Pattern Detection: Covers 64 vulnerability patterns across 16 categories including prompt injection, data exfiltration, and privilege escalation.
- Flexible Inputs: Accepts Git repositories, URLs, zip files, directories, and single files for scanning.
- Fast Static Checks: Runs rapid static analysis by default to flag risky instructions, hidden metadata, and overbroad permissions.
- Optional LLM Semantic Analysis: Adds intent-comparison analysis powered by an LLM for issues that need deeper reasoning.
- Supply-Chain & MCP Coverage: Detects supply-chain attacks, memory poisoning, tool misuse, trigger abuse, and MCP-specific risks.
- Taint Tracking & YARA Signatures: Uses taint tracking and YARA signatures to catch dangerous code paths.
Best for
- Pre-Install Skill Vetting: Scan an agent skill before installation to decide whether it is safe to use.
- Marketplace Review: Automate risk scanning inside a skill publishing or catalog pipeline.
- Security Audits: Audit existing agent skills for prompt injection and data exfiltration risks.
- Supply-Chain Defense: Detect malicious or over-permissioned skills introduced through third-party sources.