Jaayden Halko
bc44cdda75
closes CODAGT-203
## Summary
`list_templates` now returns a ranked shortlist with a recommendation,
so the chat agent can pick the right template the way a colleague would:
prefer what matches the request, what the user already uses, and what
the rest of the organization uses. Instead of teaching the model an enum
protocol in prompts, every result carries a fixed `next_step`
instruction telling the agent what to do.
## How list_templates works
1. **Fetch**: active, non-deprecated templates in the chat's
organization, filtered by the admin template allowlist, authorized as
the chat owner (no system escalation).
2. **Query relevance** (optional `query` argument): each template
receives the highest tier any of its fields matches, and a higher tier
always outranks a lower one regardless of usage:
| Tier | Match |
|------|-------|
| 4 | name or display name equals the query |
| 3 | name or display name starts with the query |
| 2 | name or display name contains the query |
| 1 | description contains the query (checked only when no name field
matched) |
| 0 | no match; the template is excluded |
Matching is case-insensitive and ignores spaces/hyphens/underscores
(`python gpu` matches `python-gpu`).
3. **Usage signals**: a new `GetTemplateRankingSignalsByOwnerID` query
returns, per template, the owner's active and recently-deleted workspace
counts within a 60-day window, the last in-window usage, and the count
of distinct developers with an active workspace (unclaimed prebuilds
excluded).
4. **Affinity score** (computed in Go, per template, from that
template's signals only):
```text
affinity = 10 x (active + 0.5 x deleted) x 0.5^(days_since_last_use /
14)
+ ln(1 + active_developers)
```
`active`/`deleted` are the owner's in-window workspace counts,
`days_since_last_use` is measured from the most recent in-window usage
(the personal term is zero without in-window usage), and
`active_developers` is the org-wide count. Personal usage carries 10x
the weight of org popularity; the confidence floor is the score of two
active developers (`ln 3`) and the required lead over the runner-up is
`ln 3 - ln 2`.
5. **Rank**: query tier first (when a query is present), then affinity
score, then name/ID for determinism. Results paginate 10 per page with
`next_page` present only when more exist.
## Recommendation contract
The result tells the agent what to do next instead of describing
confidence levels:
- `recommended_template_id` is present only when the top template is a
clear winner: the only available template, a decisive query match, or an
affinity score that clears a floor and leads the runner-up by a derived
margin.
- `next_step` is always present and is one of four fixed sentences: use
the recommendation, ask the user to choose, retry a query that matched
nothing, or report that no templates are available.
Per-template items carry raw evidence (`active_developers`,
`your_workspace_count`, `last_used_by_you`) rather than derived labels.
When signals fail to load, the tool logs and degrades to asking the user
unless the query alone is decisive.
Prompts and the `create_workspace`/`read_template` descriptions
reference the field through the `chattool.NextStepField` constant, so
the instruction lives in one place and cannot drift. `create_workspace`
remains idempotent and allowlist-enforced.
## Authorization
The signals query runs with the chat owner's permissions: reading the
owner's own workspaces plus a template-metadata read for the cross-user
popularity count. dbauthz rejects the call if any requested template is
not readable by the owner (covered by allow and deny method tests).
## Docs
Adds `docs/ai-coder/agents/tools/` explaining how agent tool calls work,
with `list_templates` ranking and the `next_step` contract as the first
documented tools.
About
Coder is a self-hosted platform for running AI coding agents and cloud development environments on infrastructure you control. It works with any cloud, IDE, OS, Git provider, and IDP.
Coder Workspaces
Coder Workspaces are cloud development environments defined with Terraform, connected through a secure Wireguard tunnel, and automatically shut down when not in use. Agents and developers share the same workspace infrastructure.
- Defined in Terraform: Templates describe the infrastructure for each workspace, from EC2 VMs and Kubernetes Pods to Docker containers.
- Any architecture and OS: Support ARM and x86-64 across Windows, Linux, and macOS from a single deployment.
- Managed by admins: Platform teams create and maintain templates that enforce approved images, resource limits, and security policies.
- Accessed from any IDE: Connect through VS Code, JetBrains, Cursor, a web terminal, remote desktop, or SSH.
- Automatic shutdown: Idle workspaces stop automatically to reduce cloud spend, and restart in seconds when needed.
Coder Agents
Coder Agents is a native AI coding agent built into Coder. The agent loop runs in the Coder control plane on your infrastructure, not in the workspace and not in a vendor's cloud. Developers interact with agents through the web UI or the REST API for programmatic and CI-driven workflows.
- Self-hosted agent loop: The control plane handles planning, model calls, and tool dispatch. Workspaces have zero AI awareness.
- No API keys in workspaces: LLM credentials stay in the control plane.
- Any model: Anthropic, OpenAI, Google, Bedrock, or self-hosted endpoints. Switching is a configuration change.
- Governance and cost controls: Centralized model approval, per-user spend limits, and audit logging.
- Open source and inspectable: The full platform is available to audit and extend.
IDE support
You can use:
-
Any Web IDE, such as
- code-server
- JetBrains Projector
- Jupyter
- And others
-
Your existing remote development environment:
-
A file sync such as Mutagen
Why remote development
Provisioning consistent development environments for a large engineering team is difficult. Each developer has preferences for operating systems, editors, and toolchains, and ensuring a reliable build environment across all of them is a maintenance burden. A missed step during onboarding or an unsupported local configuration can cost hours of debugging.
Remote development solves this by moving the environment off the developer's machine and into managed infrastructure. The developer's laptop becomes a portal into the actual compute where work happens. If a device is lost or replaced, access is simply revoked; no source code or credentials are stored locally.
This approach provides:
- Speed: Server-grade hardware accelerates builds, tests, and large workloads without requiring expensive local machines.
- Consistency: Infrastructure tools such as Terraform, nix, Docker, and Dev Containers produce identical environments for every developer.
- Security: Source code stays on private servers. Users and groups are managed through SSO and RBAC.
- Compatibility: Workspaces share infrastructure configurations with staging and production, reducing configuration drift.
- Accessibility: Browser-based IDEs and remote IDE extensions let developers work from any device, including lightweight laptops, Chromebooks, and tablets.
Read more on the Coder blog, the Slack engineering blog, or from Alex Ellis at OpenFaaS.
Why Coder
The key difference between Coder and other platforms is that the entire system, agent loop, control plane, model routing, and workspace provisioning, runs on infrastructure you control.
For agents, this means platform teams can:
- Run the entire agent loop on their infrastructure, with no SaaS dependency for orchestration.
- Define MCP servers, skills, and system prompts centrally so every agent session starts with the same tools, policies, and context.
- Keep LLM credentials out of workspaces entirely.
- Tie every agent action to an authenticated user identity.
- Support air-gapped and restricted-network deployments with self-hosted models.
For workspaces, this means admins can:
- Support any architecture (ARM, x86-64) and operating system (Windows, Linux, macOS).
- Modify pod/container specs, such as adding disks, managing network policies, or setting/updating environment variables.
- Use VM or dedicated workspaces, developing with Kernel features (no container knowledge required).
- Enable persistent workspaces, which are like local machines, but faster and hosted by a cloud service.
Pricing
Coder is free and open source under the GNU Affero General Public License v3.0. All developer productivity features are included in the open source version. A Premium license is available for enhanced support and custom deployments.
How Coder works
Coder workspaces are represented with Terraform, but you do not need to know Terraform to get started. The Coder Registry provides production-ready templates for AWS EC2, Azure, Google Cloud, Kubernetes, and other providers.
Providers and compute environments
Workspaces can include more than just compute. Terraform can add storage buckets, secrets, sidecars, and other resources.
See the templates documentation for details.
What Coder is not
-
Coder is not an infrastructure as code (IaC) platform.
- Terraform is the first IaC provisioner in Coder, allowing Coder admins to define Terraform resources as Coder workspaces.
-
Coder is not a DevOps/CI platform.
- Coder workspaces can be configured to follow best practices for cloud-service-based workloads, but Coder is not responsible for how you define or deploy the software you write.
-
Coder is not an online IDE.
- Coder supports common editors, such as VS Code, vim, and JetBrains, all over HTTPS or SSH.
-
Coder is not a collaboration platform.
- You can use Git with your favorite Git platform and dedicated IDE extensions for pull requests, code reviews, and pair programming.
-
Coder is not a SaaS/fully-managed offering.
- Coder is a self-hosted solution. You must host Coder in a private data center or on a cloud service, such as AWS, Azure, or GCP.