Extending xdge Skills

When we first launched Skills by xdge, it consisted of two core building blocks:

• Workflows — structured, multi-step automation
• Prompts — reusable reasoning units for search, analysis, and generation

Both were powerful. Both were flexible.

But neither had direct access to a stable, production-grade action layer. If a Workflow or Prompt needed to take action, post to Slack, update Salesforce, or create a document, the system dynamically generated the required tool at runtime.

It worked. It felt magical. But it wasn’t how production systems scale.

Today, we’re introducing Tools, a third dimension of Skills, launching with 100+ prebuilt, certified actions that Workflows and Prompts can now call directly.

The Original Model: AI Generating Tools at Runtime

In the first generation of Skills, execution worked like this:

You describe what needs to happen. The system reasons through it.
If a required tool didn’t exist, the code generator would build it on the fly.

Under the hood, it would:

• Interpret the API
• Infer input/output schemas
• Generate integration logic
• Test execution
• Retry if needed
• Run safely

This unlocked enormous flexibility. We weren’t constrained by a fixed catalog of actions, the system could synthesize what didn’t exist.

But there was a structural cost.

Every time a Workflow ran, for every tenant and every user, parts of the execution layer had to be rebuilt in real time. Even with guardrails and validation loops, that introduced latency and variability.

Common workflows could take 10–15 minutes to complete.
Results were correct, but execution wasn’t deterministic.

For enterprise systems, that distinction matters.

Introducing Tools as a Third Dimension of Skills

Until now, Skills had two dimensions:

• Workflows — orchestration
• Prompts — reasoning

That combination allowed teams to analyze and coordinate work across systems.

What it lacked was a persistent, production-grade execution layer.

Tools are that third dimension.

Instead of dynamically generating common tools at runtime, we:

• Took the same reasoning engine used in dynamic generation
• Ran it offline at scale
• Put developers in the loop
• Standardized schemas and I/O contracts
• Hardened and QA-certified behavior
• Implemented directly in our backend

The result: 100+ production-grade, prebuilt tools available out of the box.

Most importantly:

Workflows and Prompts can now call Tools directly.

Reasoning lives in Prompts.
Orchestration lives in Workflows.
Deterministic execution lives in Tools.

Architectural Shift: Prebuilt Core Actions + AI for Custom Logic

Here’s what changed structurally.

Previously

• Skills = Workflows + Prompts
• Actions generated dynamically at runtime
• Tool synthesis embedded inside execution loops
• Retry and validation inside code-generation cycles

Now

• Skills = Workflows + Prompts + Tools
• High-frequency actions implemented as backend services
• Structured and standardized input/output contracts
• Stable, repeatable execution paths
• Code generator focused on long-tail and custom logic

Repeatable, high-frequency work is handled by certified backend Tools.

The AI generator is reserved for:

• Custom glue logic between systems
• Rare edge cases
• Specialized transformations
• Novel workflows that don’t justify a prebuilt primitive

This separation is intentional. It’s how you get speed and flexibility without sacrificing reliability.

10–15 Minutes to 1–2 Minutes: Faster, Predictable Execution

With Tools in place:

• Workflow execution drops from 10–15 minutes to 1–2 minutes for common paths
• Results are consistent across tenants and runs
• Observability improves
• Enterprise trust increases

Workflows feel faster because they no longer rebuild their action layer on each run.

Prompts become more powerful because they can now trigger deterministic execution directly, not just reason about outcomes.

AI moves from analysis to action without introducing variability into the system.

What’s Included in the 100+ Tool Launch

The first 100+ Tools focus on high-frequency, business-critical actions across the systems teams use every day.

Salesforce

• Change opportunity stage
• Update opportunity fields
• Create or update tasks
• Add notes or follow-ups

Jira

• Add a comment
• Change issue status
• Reassign an issue
• Update fields

Gmail

• Add or remove labels
• Draft an email
• Send templated replies
• Organize threads

Slack & Microsoft Teams

• Post a message to a channel
• Send direct messages
• Trigger structured updates

Documents & Content

• Create Google Docs
• Generate Word documents
• Structure documents from templates
• Populate content dynamically

These are the actions that typically follow reasoning:

Analyze → Decide → Act

Now, those action steps are prebuilt, certified, and directly callable.

Browsable in skills.xdge.ai

Executable in app.xdge.ai

Tools aren’t hidden infrastructure. They are visible, discoverable building blocks inside Skills.

You can:

• Browse the growing catalog at skills.xdge.ai
• Understand each tool’s input/output contract
• See examples of usage
• Call them directly inside app.xdge.ai via Workflows or Prompts

This makes Tools durable assets, not ephemeral code generated during execution.

They are searchable.
They are versioned.
They are reusable across teams.

And because they’re standardized, every Workflow and Prompt can rely on deterministic behavior.

From AI to Infrastructure

The first version of Skills proved that natural language could orchestrate real work across enterprise systems.

This version makes it dependable.

AI can generate impressive results.
Infrastructure delivers consistent outcomes.

By introducing Tools as a certified execution layer inside Skills, we’ve shifted from dynamic generation everywhere to a structured, layered system:

• Prompts handle reasoning
• Workflows handle orchestration
• Tools handle deterministic execution
• Common actions are prebuilt and production-grade
• Custom logic is generated only where flexibility is required

This is how AI platforms mature, not by removing flexibility, but by putting structure around it.

Scaling the Tools Layer

Today: 100+ prebuilt tools.
Next: hundreds more.

We’re expanding across connectors and deepening capabilities inside each integration. The roadmap moves from dozens of apps toward 100+ apps and 1,000+ connectors.

The vision remains the same:
Natural language as the control plane for enterprise systems.

What changed is the execution foundation.

If you’ve ever thought, “This should be automated.”

You’re right.

Now, Workflows and Prompts can call certified Tools directly and execute fast enough, and predictably enough, to depend on them.