Swiftask analyzes your GitHub repositories to write, structure, and update your technical documentation. Your READMEs and wikis stay in sync with your code.
Result:
Stop wasting time on manual writing. Your documentation is always accurate and ready for your users.
Stop wasting time on manual writing. Your documentation is always accurate and ready for your users.
Technical documentation is often outdated
Code evolves faster than documentation. Developers prioritize feature delivery, leaving documentation behind. The result: invisible technical debt, difficult onboarding, and a loss of critical team knowledge.
Main negative impacts:
Swiftask connects your GitHub repositories to a specialized AI agent. It reads your commits, analyzes your functions, and automatically updates your documentation files. You stay in control, the AI handles the writing.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
A developer deploys a new feature. They forget to update the README file. Other team members have to read the source code to understand the changes. Misunderstandings pile up.
With Swiftask + GitHub
As soon as a Pull Request is merged, Swiftask analyzes the changes, updates the relevant documentation in your GitHub repository, and notifies the team. Your documentation is always a faithful reflection of your codebase.
How to automate your documentation in 4 steps
STEP 1 : Connect your GitHub repository
Grant Swiftask access to your repositories. Read-only access is sufficient to start analyzing your code.
STEP 2 : Define writing rules
Configure the style, format (Markdown, HTML), and sections to monitor in your documentation.
STEP 3 : Configure triggers
Choose when the agent should intervene: after every merge, upon version tagging, or on demand via a command.
STEP 4 : Validation and publishing
The agent proposes a documentation update via a Pull Request. You review, approve, and it's published.
Documentation agent key features
The agent analyzes code changes, commit messages, and function signatures to extract business logic.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-github@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why automate with Swiftask
1. Living documentation
Your documentation evolves alongside your code, without manual intervention.
2. Productivity gains
Free your developers from writing tasks so they can focus on coding.
3. Standardization
All your documentation follows the same format and quality, regardless of the code author.
4. Reduced technical debt
Clear documentation reduces errors and facilitates long-term maintenance.
5. Easier collaboration
Non-technical teams can understand changes through automatically generated summaries.
Security and privacy
Swiftask applies enterprise-grade security standards for your github automations.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your development cycle
| Metric | Before | After |
|---|---|---|
| Doc update time | Several hours per sprint | Automated (seconds) |
| Doc accuracy | Variable (risk of oversight) | 100% correlated to code |
| Onboarding speed | Slow (lack of info) | Accelerated (comprehensive doc) |
| Documentation debt | High | Near zero |
Take action with github
Stop wasting time on manual writing. Your documentation is always accurate and ready for your users.
Swiftask connects your GitHub repositories to a specialized AI agent. It reads your commits, analyzes your functions, and automatically updates your documentation files. You stay in control, the AI handles the writing.
The agent analyzes code changes, commit messages, and function signatures to extract business logic.
Security is a priority: Swiftask does not store your source code beyond what is necessary for generation.
Next use case
Automatically generate GitHub Pull Request summaries with your AI agents
Discover the next available use case for github.
View next use case