Skillsize

Skillsize is a platform for turning an organisation’s methods, frameworks and expert judgement into reusable AI Skills. Its official product site describes a no-code workflow for building, publishing and deploying structured AI capabilities that can analyse, assess, decide and produce work according to a defined methodology.

What Skillsize — Turn your expertise into executable does

Skillsize is designed to capture not only source knowledge, but also how experts use evidence, apply criteria, sequence reasoning and make decisions. Users can provide documents, notes, data and a brief, then define the method, constraints, review points and desired deliverable. The resulting Skill is intended to reproduce a firm’s methodology rather than rely on a single prompt or improvised model response.

The platform describes support for structured reasoning stages such as analysis, comparison, evaluation, judgement and synthesis. It also includes human review gates so people can inspect evidence, challenge analysis and approve decisions before a workflow continues. Skillsize says outputs can include reports, memos, assessment packs and other structured professional deliverables, with the underlying work and methodology traceable for review, governance or audit.

Notable capabilities

• No-code Skill creation: Build, publish and deploy AI Skills without coding or maintaining prompts.
• Sequenced methodology: Organise work into defined reasoning stages with evidence requirements and decision logic.
• Human-in-the-loop review: Add approval points at critical stages before the AI proceeds or produces a final outcome.
• Traceable execution: Review what evidence was considered, how the work was performed and how conclusions were reached.
• Portability and data controls: Export Skills for environments including ChatGPT, Claude, Microsoft Copilot and other AI products through formats or interfaces the vendor identifies as SKILL.md and MCP; Skillsize also describes PII stripping and pseudonymisation before processing by underlying models.

How it fits a workflow

A typical workflow starts with uploading a question, challenge, supporting documents and evidence. Users can then assemble the relevant Skills, or let Skillsize determine a combination for the work, before running the defined methodology. The final step turns the analysis into a structured deliverable while retaining a traceable record of the reasoning and methodology. Skills may be used across teams and engagements, embedded in operational workflows or packaged as standalone client-facing experiences.

Who it helps

Skillsize is aimed at people whose expertise is central to the work they deliver. Its stated audiences include independent consultants, advisors and coaches, professional-services firms, and internal specialists who want to turn proprietary methods or organisational knowledge into repeatable AI capabilities. Potential applications include structured assessments, diagnostics, decision tools, benchmarks, engagement delivery and operational workflows.

Strengths and limits

The product’s stated strength is controlled, repeatable execution of expert methods rather than general-purpose conversation. Defined inputs, evidence requirements, staged reasoning and human review may fit work where consistency and auditability matter. Its model-independent positioning is intended to keep a methodology portable as underlying AI environments change.

The available source material does not provide pricing, independent performance measurements or details about implementation requirements. The platform’s claims about reducing hallucination risk, protecting sensitive data and reproducing expert judgement should therefore be understood as stated product capabilities, not independently verified outcomes.