Standardize
Skills, rules, hooks, subagents and MCP servers: the five Artifact types, packaged into one named, versioned Kit.
See how Kits are composedThe governance hubfor AI tooling.
Your AI tooling: standardized, distributed across your organization, and measured so you can decide with data.
Your organization
Illustrative sampleAI involvement in commits
Overview
What is HubBound?
HubBound is the governance hub for AI tooling, an internal developer platform that packages your team's AI configuration into versioned Kits, distributes each Kit to the teams that need it, and measures the impact those Kits have on your code.
Distribute
Assign a Kit to one team or to the whole organization, so every group runs exactly the standard it needs.
How teams and scoping workMeasure
See how much of your codebase carries AI's fingerprints, broken down by person, tool and model.
See Measure in depthHubBound keeps growing beyond these three.
Security
Audit any Skill on demand: deterministic rules plus a model review, with a verdict and a fix for every finding.
Available todaySee Security in depthMemories, Projects and Ink
One bundle: agents capture decisions and conventions, Projects keep them shared, and Ink answers from all of it with its sources.
Available todaySee the Context BundleLive Planning
Share your coding agent's plan, edit it live with your team and approve it before it runs.
Available todaySee Live Planning in depthSupported providers
Does HubBound work with the AI tools you already use?
HubBound is provider-agnostic: the same Kit installs into Claude Code, Cursor, Codex, Copilot and Antigravity without rewriting a single rule. Your team keeps the AI tools it already uses. HubBound only adds the layer that standardizes, distributes and measures how those tools are configured.
Claude CodeCursorCodexAntigravityCopilot
The problem
What does AI tooling look like without HubBound?
Without HubBound, most companies run AI tooling with no shared standard: every developer configures prompts, rules and agents their own way, and nobody can see what changed, where, or how well it worked. The result is configuration drift across machines and zero visibility into AI's real impact on the codebase.
No standards
Every developer configures AI their own way: different rules, different agents, different conventions. What works on one machine doesn't exist on the next, and onboarding means starting from zero.
No visibility
AI is writing part of your codebase and nobody can say how much, where, or how well. Without measurement there's no way to improve, or to justify what you're paying for.
Before and after
What changes when AI tooling is governed?
HubBound governs AI tooling by replacing scattered, per-developer setups with one shared, versioned standard every machine runs the same way. The rows below show the real before-and-after of a team's configuration and visibility once that standard exists: no projected numbers, just configuration states.
Without HubBound
Different rules per developerNo version historyUntracked MCP serversManual onboarding checklistNo visibility into usageConfig drift across machines
With HubBound
One shared KitEvery change versionedMCP servers tracked centrallyOne-command onboardingFull usage visibilitySame setup on every machine
01 · Standardize
How does HubBound standardize a team's AI configuration?
HubBound packages every skill, rule, hook, subagent and MCP server your team uses into one named, versioned Kit. Instead of five different files scattered across machines, there is one place to add, edit and review each type before anything reaches a team.
Your organization
Illustrative sampleFrontend Standards KitOrganization
skills/code-review.md
Reviews a pull request diff for correctness and obvious security issues.
rules/code-style.md
Named exports only. No default exports.
mcp/postgres.json
Gives the agent read access to the production database schema.
subagents/release-notes.md
Drafts release notes from the pull requests merged this week.
hooks/pre-commit.sh
Runs lint and tests automatically before every commit.
Illustrative sample data. Kit, file and artifact names are for illustration only.
02 · Distribute
How does a Kit reach the right team?
HubBound assigns Kits to teams, not to the whole organization at once: your Frontend team gets the Frontend standard, your Platform team gets its own, and every member's role controls what they can change.
Your organization
Illustrative sampleTeams
- Frontend
- Platform
- Growth
- Data
Frontend
4 members- Alicia Moreno@alicia.morenoAdmin
- Diego Ramírez@diego.ramirezUser
- Priya Kapoor@priya.kapoorUser
- Sam Torres@sam.torresUser
- Frontend Standards KitActive
- Security Baseline KitActive
- Onboarding KitPending
Illustrative sample data. Team, member and distribution names are for illustration only.
03 · Measure
How does HubBound measure the impact of AI on your code?
HubBound measures what AI tooling actually ships: sessions, commits, pull requests and lines of code that carry evidence of AI assistance, broken down by person, tool and model over the period you choose. Engineering leads see how AI is changing the way the team delivers, instead of guessing.
Your organization
Illustrative sampleSessions
+9.6% Compared with the previous period
Tokens
+14.1% Compared with the previous period
Commits
+7.3% Compared with the previous period
Pull requests
+11.2% Compared with the previous period
Lines added
+6.8% Compared with the previous period
AI involvement in commits
Share of commits with evidence of AI assistance.
AI
Pull request outcomes
How the pull requests opened in this period ended up.
- Open · 17
- Closed · 8
- Merged · 118
Time to merge
Average hours from opening a pull request to closing it.
Activity calendar
Sessions per day across the period.
Sessions over time
AI sessions opened each day.
+9.6%
Lines added over time
Total lines added each day, and how many carry AI evidence.
+6.8%
- AI · 13,254 (34.5%)
- Other lines · 25,163 (65.5%)
Most used skills
Skills your team invokes most often.
- Code Review86
- Test Generator63
- PR Summary47
- Onboarding Guide24
Most used MCP servers
MCP servers your team connects to most often.
- GitHub214
- Postgres132
- Slack88
- Notion51
Illustrative sample data. The layout mirrors the Data tab of HubBound's analytics dashboard.
Roadmap
What is HubBound building next?
Two features are next on HubBound's roadmap: the Artifact agent and Automated Dailies. Neither ships yet, and neither has a committed date. This section names what's coming next without promising a timeline HubBound can't keep.
Artifact agent
An AI agent that creates Artifacts for your team: describe what you need and it drafts the skill, rule, hook, subagent or MCP server, ready for you to review and publish.
Not available yetAutomated Dailies
A written daily, created in a space at the start of each day, that tells the team what its AI agents did the day before.
Not available yet
See how it all connects.
Each piece of HubBound builds on the others. Pick where you want to go next.
Bring order to your AI stack.
See how HubBound can package, distribute and measure your team AI standards.
