Settings Reference
Complete guide to configuring Codistry for your workflow.
You almost never need to touch a config file. Open the Codistry sidebar in VS Code and click the settings gear at the top, the Settings view groups everything below into tabs (Models, Context Engine, Tools & Integrations, and more) with friendly toggles and inputs.
That gear is the way to configure Codistry (you can also open it from the Command Palette with Codistry: Open Settings). The keys documented below are the internal identifiers those controls write, listed so you know exactly what each control does; you don't need to set them by hand.
Provider Configuration
| Setting | Default | What it does |
|---|---|---|
modelProvider | anthropic | Which provider powers requests: anthropic · openai · custom-openai (local / corporate / OpenAI-compatible). |
openaiApiUrl | "" | Custom OpenAI-compatible endpoint (e.g. Ollama :11434/v1, LM Studio :1234/v1). Empty uses api.openai.com. |
anthropicApiUrl | "" | Custom Anthropic endpoint for proxies, regional gateways, or Bedrock. Usually left empty. |
reasoningEffort | medium | Thinking depth for reasoning models: none · minimal · low · medium · high · xhigh. Higher = slower and pricier. |
adronite-agent.model
The default model every new chat session starts with (within the selected provider). Switching the model inside a chat overrides it for that session only; this default is left untouched.
| Type | string |
| Default | claude-sonnet-4-6 |
| Task | Model | Why |
|---|---|---|
| Refactoring | claude-opus-4, gpt-5 | Deep code understanding |
| Quick Edits | claude-sonnet-4-6, gpt-5.2 | Fast and accurate |
| Complex Problems | o1, o3 | Advanced reasoning |
| Privacy/Offline | llama3-70b | No external calls |
This is a new-session default: each new chat opens with this model. Use the model picker in the chat header to switch the model for a single session. That choice is saved with the session and doesn't change this default or affect chats you've already started. See Models → Default model.
Model Management
adronite-agent.customModels
Define custom models for local LLMs, corporate endpoints, or specialized deployments.
| Type | array of model objects |
| Default | [] |
Add and edit models in Settings → Models → Add Custom Model. Each model offers:
- Basics: display name, model name, API URL, and an optional per-model API key
- Token limits: Max Tokens and Max Output Tokens
- Capabilities: reasoning, images, temperature, and streaming toggles
- Advanced Settings: sampling parameters (temperature, top-p, top-k, min-p, and repetition / frequency / presence penalties) and a reasoning/thinking format for open models
Tool support is required. Codistry only works with models that support tool/function calling, so there is no toggle to turn it off.
| Setting | Default | What it does |
|---|---|---|
disabledProviders | {} | Hide specific providers from the UI (e.g. enforce corporate policy). |
streamingEnabled | all true | Real-time token streaming per provider. Disable for local models with buggy streaming. |
Behavior & Control
adronite-agent.globalAutoApprove
Skip ALL tool approval prompts automatically.
| Type | boolean |
| Default | false |
⚠️ Use with extreme caution
The agent can modify files and run commands without permission. Never enable for production code. Use autoApproveTools for granular control instead.
adronite-agent.autoApproveTools
Granular auto-approval for specific tools by name.
| Type | object (tool → boolean) |
| Default | {} (no auto-approvals) |
🟢 Safe
read_file, find_files_by_name, grep_file_contents, list_symbols_in_file, get_file_diagnostics, get_git_status
🟡 Caution
edit_file, write_file, memory.*
🔴 Dangerous
run_shell_command, run_vscode_editor_command, run_vscode_task, rename_symbol_across_codebase
{
"adronite-agent.autoApproveTools": {
"read_file": true,
"find_files_by_name": true,
"grep_file_contents": true,
"list_symbols_in_file": true,
"get_file_diagnostics": true,
"get_git_status": true,
"edit_file": false,
"run_shell_command": false
}
}adronite-agent.autoApproveCommands
Terminal command allow-patterns (token-prefix) that run without an approval dialog.
| Type | array of strings |
| Default | [] (nothing auto-approved) |
A run_shell_command invocation that cleanly matches one of these prefixes runs without prompting. Commands containing shell control characters (;, &, |, backticks, $(), redirects) never auto-approve.
{
"adronite-agent.autoApproveCommands": ["npm test", "git status", "ls"]
}adronite-agent.denyCommands
Terminal command deny-patterns (token-prefix) that are refused outright, no dialog.
| Type | array of strings |
| Default | [] |
Deny rules are absolute: they beat every auto-approve grant and apply inside compound commands too.
{
"adronite-agent.denyCommands": ["rm -rf", "git push --force"]
}| Setting | Default | What it does |
|---|---|---|
maxIterations | 1000 | Max tool-call steps before the agent stops (1–1000). Lower it for quick, read-only tasks. |
autoApproveMcpTools | false | Auto-approve MCP tool calls — globally, or per server via autoApproveMcpServers. |
subagentsEnabled | true | Let the agent delegate focused sub-tasks to isolated agents. A built-in general-purpose agent is always available. See Agents & Subagents. |
Context & Memory
| Setting | Default | What it does |
|---|---|---|
contextRules | "" | Custom instructions added to every request (style, frameworks, testing). Keep to ~100–300 words. |
projectMemory | true | Build a persistent, local knowledge graph about your codebase for better context in later sessions. |
enableSummarization | true | Summarize older turns to preserve context. Off = sliding window that drops the oldest messages. |
enableAdaptiveLearning | true | Learn cross-project preferences (tone, standards, common corrections). Stored locally only. |
adaptiveLearningContent | "" | The learned worldview text. Auto-populated; edit it to curate what the agent remembers. |
Context Engine
adronite-agent.contextEngineEnabled
Umbrella toggle for the Adronite Context Engine: concept-graph tools, the Index settings tab, and the knowledge-graph subsystem.
| Type | boolean |
| Default | true |
One switch controls the whole engine: when on, the agent can pull in relevant context automatically, the Context Engine settings tab is active, and the code-navigation tools are enabled.
| Setting | Default | What it does |
|---|---|---|
conceptSearch2Enabled | false | Concept-graph search over files edited together in the same commits (developer preview). |
conceptSearchEmbedder | local | Embedding provider for the concept index: local · auto · openai · openrouter. |
contextPackAutoInject | true | Seed each fresh task with likely-relevant file paths (references only). A no-op without an index. |
contextPackBudget | 8000 | Token budget for the on-demand context pack (1000–32000). Doesn't affect the auto-inject seed. |
contextPackCoChange | true | Also surface frequently co-edited supporting files (a git-history signal). Additive only. |
contextIndexAutoUpdate | true | Refresh existing indexes when git HEAD changes. Never builds from scratch. |
contextIndexNotifyOnCommit | true | When auto-update is off, prompt to refresh after a commit. |
contextIndexModel | default model | Pick a specific (e.g. cheaper) model to build indexes instead of your chat model. |
fileBriefEnabled | false | Let the agent get a deterministic outline of a large file without reading it in full. |
userExpertiseEnabled | true | Share the mined User Expertise profile with the agent (a system-prompt block). The profile itself is always mined with the index. |
workSuggestionsEnabled | true | Personalized welcome-screen suggestions drawn from your recent commits (one small model call per new HEAD). |
Advanced
adronite-agent.mcpLazyLoading
"Skinny Tools": make tool usage more token-efficient.
| Type | boolean |
| Default | true |
Shown as Skinny Tools under Tools & Integrations. When on, the agent loads the full details of a tool only when it needs it, which can cut token usage significantly. Leave it on unless you notice the agent struggling to pick the right tool.
adronite-agent.skillsEnabled
Enable the Skills system for isolated Docker execution.
| Type | boolean |
| Default | true |
| Requires | Docker |
skillsDirectory: default~/.adronite/skillsskillsDockerImage: defaultadronite/adronite-skills:latestdynamicSkillsEnabled: defaulttrue; auto-captures repo-specific procedures as skills in.codistry/skills/
adronite-agent.telemetryEnabled
Anonymous usage data for improving the extension.
| Type | boolean |
| Default | true |
Collected (anonymous)
- Feature usage patterns
- Performance metrics
- Error reports (no code)
Never collected
- Source code or file contents
- Prompts or conversations
- API keys or credentials
Respects VS Code's global telemetry setting.
| Setting | Default | What it does |
|---|---|---|
mcpEnabled | true | Enable Model Context Protocol servers. Disable for air-gapped or locked-down setups. See the MCP Extensions guide. |
showSidebarOnLaunch | true | Open and focus the Codistry sidebar when VS Code starts. |
Account & License
The Account section in Settings shows:
- Email, Licensed badge, active session status
- License token validity and expiration
- Active plan and next renewal date
- Manage Subscription: opens your billing portal
The Developer tier is free, no subscription required when using your own API keys.
Configuration examples
Three common setups, expressed as what to change in the settings UI (gear icon → the named tab):
Local development (privacy-first)
- Models → add an OpenAI-compatible model pointing at your local server (e.g. http://localhost:11434/v1) and select it.
- Approval → auto-approve the read-only tools you trust (read file, find files, list symbols).
Enterprise / corporate
- Models → OpenAI provider with your company gateway as the API URL (e.g. https://ai.mycompany.com/v1).
- General → raise Max Iterations if your tasks are long (e.g. 20).
- Approval → leave auto-approvals empty so every action is confirmed.
- General → turn off Enable Telemetry.
- Personalization → put company guidelines in Custom Rules.
Maximum privacy
- Models → a local model through Ollama or LM Studio; no cloud provider configured.
- General → turn off Enable Telemetry.
- Tools & Integrations → turn off MCP and Skills.
- Personalization → turn off Adaptive Learning.
Check out Best Practices for optimization tips or the FAQ for common questions.