CSC Best Practices

Tips and patterns for getting the most out of CSC, from configuring your environment to scaling across parallel sessions.

CSC is an agentic coding environment. Unlike a chatbot that answers questions and waits, CSC can read your files, run commands, make changes, and autonomously work through problems while you watch, redirect, or step away entirely.

This changes how you work. Instead of writing code yourself and asking CSC to review it, you describe what you want and CSC figures out how to build it. CSC explores, plans, and implements.

But this autonomy still comes with a learning curve. CSC works within certain constraints you need to understand.

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Most best practices are based on one constraint: CSC's context window fills up fast, and performance degrades as it fills.

CSC's context window holds your entire conversation, including every message, every file CSC reads, and every command output. However, this can fill up fast. A single debugging session or codebase exploration might generate and consume tens of thousands of tokens.

This matters since LLM performance degrades as context fills. When the context window is getting full, CSC may start "forgetting" earlier instructions or making more mistakes. The context window is the most important resource to manage. To see how a session fills up in practice, watch an interactive walkthrough of what loads at startup and what each file read costs. Track context usage continuously with a custom status line, and see Reduce token usage for strategies on reducing token usage.

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Give CSC a way to verify its work

💡 Tip: Include tests, screenshots, or expected outputs so CSC can check itself. This is the single highest-leverage thing you can do.

CSC performs dramatically better when it can verify its own work, like run tests, compare screenshots, and validate outputs.

Without clear success criteria, it might produce something that looks right but actually doesn't work. You become the only feedback loop, and every mistake requires your attention.

Strategy	Before	After
Provide verification criteria	"implement a function that validates email addresses"	"write a validateEmail function. example test cases: user@example.com is true, invalid is false, user@.com is false. run the tests after implementing"
Verify UI changes visually	"make the dashboard look better" "[paste screenshot] implement this design. take a screenshot of the result and compare it to the original. list differences and fix them"
Address root causes, not symptoms	"the build is failing"	"the build fails with this error: [paste error]. fix it and verify the build succeeds. address the root cause, don't suppress the error"

UI changes can be verified using the Chrome extension for CSC. It opens new tabs in your browser, tests the UI, and iterates until the code works.

Your verification can also be a test suite, a linter, or a Bash command that checks output. Invest in making your verification rock-solid.

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Explore first, then plan, then code

💡 Tip: Separate research and planning from implementation to avoid solving the wrong problem.

Letting CSC jump straight to coding can produce code that solves the wrong problem. Use Plan Mode to separate exploration from execution.

The recommended workflow has four phases:

Explore

Enter Plan Mode. CSC reads files and answers questions without making changes.

read /src/auth and understand how we handle sessions and login.
also look at how we manage environment variables for secrets.

Plan

Ask CSC to create a detailed implementation plan.

I want to add Google OAuth. What files need to change?
What's the session flow? Create a plan.

Press Ctrl+G to open the plan in your text editor for direct editing before CSC proceeds.

Implement

Switch back to Normal Mode and let CSC code, verifying against its plan.

implement the OAuth flow from your plan. write tests for the
callback handler, run the test suite and fix any failures.

Commit

Ask CSC to commit with a descriptive message and create a PR.

commit with a descriptive message and open a PR

Note: Plan Mode is useful, but also adds overhead. For tasks where the scope is clear and the fix is small (like fixing a typo, adding a log line, or renaming a variable) ask CSC to do it directly. Planning is most useful when you're uncertain about the approach, when the change modifies multiple files, or when you're unfamiliar with the code being modified. If you could describe the diff in one sentence, skip the plan.

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Provide specific context in your prompts

💡 Tip: The more precise your instructions, the fewer corrections you'll need.

CSC can infer intent, but it can't read your mind. Reference specific files, mention constraints, and point to example patterns.

Strategy	Before	After
Scope the task. Specify which file, what scenario, and testing preferences.	"add tests for foo.py"	"write a test for foo.py covering the edge case where the user is logged out. avoid mocks."
Point to sources. Direct CSC to the source that can answer a question.	"why does ExecutionFactory have such a weird api?"	"look through ExecutionFactory's git history and summarize how its api came to be"
Reference existing patterns. Point CSC to patterns in your codebase.	"add a calendar widget"	"look at how existing widgets are implemented on the home page to understand the patterns. HotDogWidget.php is a good example. follow the pattern to implement a new calendar widget that lets the user select a month and paginate forwards/backwards to pick a year. build from scratch without libraries other than the ones already used in the codebase."
Describe the symptom. Provide the symptom, the likely location, and what "fixed" looks like.	"fix the login bug"	"users report that login fails after session timeout. check the auth flow in src/auth/, especially token refresh. write a failing test that reproduces the issue, then fix it"

Vague prompts can be useful when you're exploring and can afford to course-correct. A prompt like "what would you improve in this file?" can surface things you wouldn't have thought to ask about.

Provide rich content

💡 Tip: Use @ to reference files, paste screenshots/images, or pipe data directly.

You can provide rich data to CSC in several ways:

• Reference files with @ instead of describing where code lives. CSC reads the file before responding.
• Paste images directly. Copy/paste or drag and drop images into the prompt.
• Give URLs for documentation and API references. Use /permissions to allowlist frequently-used domains.
• Pipe in data by running cat error.log | csc to send file contents directly.
• Let CSC fetch what it needs. Tell CSC to pull context itself using Bash commands, MCP tools, or by reading files.

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Configure your environment

A few setup steps make CSC significantly more effective across all your sessions. For a full overview of extension features and when to use each one, see Extend CSC.

Write an effective AGENTS.md

💡 Tip: Run /init to generate a starter AGENTS.md file based on your current project structure, then refine over time.

AGENTS.md is a special file that CSC reads at the start of every conversation. Include Bash commands, code style, and workflow rules. This gives CSC persistent context it can't infer from code alone.

The /init command analyzes your codebase to detect build systems, test frameworks, and code patterns, giving you a solid foundation to refine.

There's no required format for AGENTS.md files, but keep it short and human-readable. For example:

# Code style
- Use ES modules (import/export) syntax, not CommonJS (require)
- Destructure imports when possible (eg. import { foo } from 'bar')

# Workflow
- Be sure to typecheck when you're done making a series of code changes
- Prefer running single tests, and not the whole test suite, for performance

AGENTS.md is loaded every session, so only include things that apply broadly. For domain knowledge or workflows that are only relevant sometimes, use Skills instead. CSC loads them on demand without bloating every conversation.

Keep it concise. For each line, ask: "Would removing this cause CSC to make mistakes?" If not, cut it. Bloated AGENTS.md files cause CSC to ignore your actual instructions!

✅ Include	❌ Exclude
Bash commands CSC can't guess	Anything CSC can figure out by reading code
Code style rules that differ from defaults	Standard language conventions CSC already knows
Testing instructions and preferred test runners	Detailed API documentation (link to docs instead)
Repository etiquette (branch naming, PR conventions)	Information that changes frequently
Architectural decisions specific to your project	Long explanations or tutorials
Developer environment quirks (required env vars)	File-by-file descriptions of the codebase
Common gotchas or non-obvious behaviors	Self-evident practices like "write clean code"

If CSC keeps doing something you don't want despite having a rule against it, the file is probably too long and the rule is getting lost. If CSC asks you questions that are answered in AGENTS.md, the phrasing might be ambiguous. Treat AGENTS.md like code: review it when things go wrong, prune it regularly, and test changes by observing whether CSC's behavior actually shifts.

You can tune instructions by adding emphasis (e.g., "IMPORTANT" or "YOU MUST") to improve adherence. Check AGENTS.md into git so your team can contribute. The file compounds in value over time.

AGENTS.md files can import additional files using @path/to/import syntax:

See @README.md for project overview and @package.json for available npm commands.

# Additional Instructions
- Git workflow: @docs/git-instructions.md
- Personal overrides: @~/.costrict/my-project-instructions.md

You can place AGENTS.md files in several locations:

• Home folder (~/.costrict/AGENTS.md): applies to all CSC sessions
• Project root (./AGENTS.md): check into git to share with your team
• Project root (./AGENTS.local.md): personal project-specific notes; add this file to your .gitignore so it isn't shared with your team
• Parent directories: useful for monorepos where both root/AGENTS.md and root/foo/AGENTS.md are pulled in automatically
• Child directories: CSC pulls in child AGENTS.md files on demand when working with files in those directories

Configure permissions

💡 Tip: Use auto mode to let a classifier handle approvals, /permissions to allowlist specific commands, or /sandbox for OS-level isolation. Each reduces interruptions while keeping you in control.

By default, CSC requests permission for actions that might modify your system: file writes, Bash commands, MCP tools, etc. This is safe but tedious. After the tenth approval you're not really reviewing anymore, you're just clicking through. There are three ways to reduce these interruptions:

• Auto mode: a separate classifier model reviews commands and blocks only what looks risky: scope escalation, unknown infrastructure, or hostile-content-driven actions. Best when you trust the general direction of a task but don't want to click through every step
• Permission allowlists: permit specific tools you know are safe, like npm run lint or git commit
• Sandboxing: enable OS-level isolation that restricts filesystem and network access, allowing CSC to work more freely within defined boundaries

Read more about permission modes, permission rules, and sandboxing.

Use CLI tools

💡 Tip: Tell CSC to use CLI tools like gh, aws, gcloud, and sentry-cli when interacting with external services.

CLI tools are the most context-efficient way to interact with external services. If you use GitHub, install the gh CLI. CSC knows how to use it for creating issues, opening pull requests, and reading comments. Without gh, CSC can still use the GitHub API, but unauthenticated requests often hit rate limits.

CSC is also effective at learning CLI tools it doesn't already know. Try prompts like Use 'foo-cli-tool --help' to learn about foo tool, then use it to solve A, B, C.

Connect MCP servers

💡 Tip: Run csc mcp add to connect external tools like Notion, Figma, or your database.

With MCP servers, you can ask CSC to implement features from issue trackers, query databases, analyze monitoring data, integrate designs from Figma, and automate workflows.

Set up Hooks

💡 Tip: Use Hooks for actions that must happen every time with zero exceptions.

Hooks run scripts automatically at specific points in CSC's workflow. Unlike AGENTS.md instructions which are advisory, Hooks are deterministic and guarantee the action happens.

CSC can write Hooks for you. Try prompts like "Write a hook that runs eslint after every file edit" or "Write a hook that blocks writes to the migrations folder." Edit .costrict/settings.json directly to configure Hooks by hand, and run /hooks to browse what's configured.

Create Skills

💡 Tip: Create SKILL.md files in .costrict/skills/ to give CSC domain knowledge and reusable workflows.

Skills extend CSC's knowledge with information specific to your project, team, or domain. CSC applies them automatically when relevant, or you can invoke them directly with /skill-name.

Create a skill by adding a directory with a SKILL.md to .costrict/skills/:

---
name: api-conventions
description: REST API design conventions for our services
---
# API Conventions
- Use kebab-case for URL paths
- Use camelCase for JSON properties
- Always include pagination for list endpoints
- Version APIs in the URL path (/v1/, /v2/)

Skills can also define repeatable workflows you invoke directly:

---
name: fix-issue
description: Fix a GitHub issue
disable-model-invocation: true
---
Analyze and fix the GitHub issue: $ARGUMENTS.

1. Use `gh issue view` to get the issue details
2. Understand the problem described in the issue
3. Search the codebase for relevant files
4. Implement the necessary changes to fix the issue
5. Write and run tests to verify the fix
6. Ensure code passes linting and type checking
7. Create a descriptive commit message
8. Push and create a PR

Run /fix-issue 1234 to invoke it. Use disable-model-invocation: true for workflows with side effects that you want to trigger manually.

Create custom Subagents

💡 Tip: Define specialized assistants in .costrict/agents/ that CSC can delegate to for isolated tasks.

Subagents run in their own context with their own set of allowed tools. They're useful for tasks that read many files or need specialized focus without cluttering your main conversation.

---
name: security-reviewer
description: Reviews code for security vulnerabilities
tools: Read, Grep, Glob, Bash
model: opus
---
You are a senior security engineer. Review code for:
- Injection vulnerabilities (SQL, XSS, command injection)
- Authentication and authorization flaws
- Secrets or credentials in code
- Insecure data handling

Provide specific line references and suggested fixes.

Tell CSC to use Subagents explicitly: "Use a subagent to review this code for security issues."

Install Plugins

💡 Tip: Run /plugin to browse the marketplace. Plugins add Skills, tools, and integrations without configuration.

Plugins bundle Skills, Hooks, Subagents, and MCP servers into a single installable unit from the community and CoStrict. If you work with a typed language, install a code intelligence plugin to give CSC precise symbol navigation and automatic error detection after edits.

For guidance on choosing between Skills, Subagents, Hooks, and MCP, see Extend CSC.

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Communicate effectively

The way you communicate with CSC significantly impacts the quality of results.

Ask codebase questions

💡 Tip: Ask CSC questions you'd ask a senior engineer.

When onboarding to a new codebase, use CSC for learning and exploration. You can ask CSC the same sorts of questions you would ask another engineer:

• How does logging work?
• How do I make a new API endpoint?
• What does async move { ... } do on line 134 of foo.rs?
• What edge cases does CustomerOnboardingFlowImpl handle?
• Why does this code call foo() instead of bar() on line 333?

Using CSC this way is an effective onboarding workflow, improving ramp-up time and reducing load on other engineers. No special prompting required: ask questions directly.

Let CSC interview you

💡 Tip: For larger features, have CSC interview you first. Start with a minimal prompt and ask CSC to interview you using the AskUserQuestion tool.

CSC asks about things you might not have considered yet, including technical implementation, UI/UX, edge cases, and tradeoffs.

I want to build [brief description]. Interview me in detail using the AskUserQuestion tool.

Ask about technical implementation, UI/UX, edge cases, concerns, and tradeoffs. Don't ask obvious questions, dig into the hard parts I might not have considered.

Keep interviewing until we've covered everything, then write a complete spec to SPEC.md.

Once the spec is complete, start a fresh session to execute it. The new session has clean context focused entirely on implementation, and you have a written spec to reference.

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Manage your session

Conversations are persistent and reversible. Use this to your advantage!

Course-correct early and often

💡 Tip: Correct CSC as soon as you notice it going off track.

The best results come from tight feedback loops. Though CSC occasionally solves problems perfectly on the first attempt, correcting it quickly generally produces better solutions faster.

• Esc: stop CSC mid-action with the Esc key. Context is preserved, so you can redirect.
• Esc + Esc or /rewind: press Esc twice or run /rewind to open the rewind menu and restore previous conversation and code state, or summarize from a selected message.
• "Undo that": have CSC revert its changes.
• /clear: reset context between unrelated tasks. Long sessions with irrelevant context can reduce performance.

If you've corrected CSC more than twice on the same issue in one session, the context is cluttered with failed approaches. Run /clear and start fresh with a more specific prompt that incorporates what you learned. A clean session with a better prompt almost always outperforms a long session with accumulated corrections.

Manage context aggressively

💡 Tip: Run /clear between unrelated tasks to reset context.

CSC automatically compacts conversation history when you approach context limits, which preserves important code and decisions while freeing space.

During long sessions, CSC's context window can fill with irrelevant conversation, file contents, and commands. This can reduce performance and sometimes distract CSC.

• Use /clear frequently between tasks to reset the context window entirely
• When auto compaction triggers, CSC summarizes what matters most, including code patterns, file states, and key decisions
• For more control, run /compact <instructions>, like /compact Focus on the API changes
• To compact only part of the conversation, use Esc + Esc or /rewind, select a message checkpoint, and choose Summarize from here. This condenses messages from that point forward while keeping earlier context intact.
• Customize compaction behavior in AGENTS.md with instructions like "When compacting, always preserve the full list of modified files and any test commands" to ensure critical context survives summarization
• For quick questions that don't need to stay in context, use /btw. The answer appears in a dismissible overlay and never enters conversation history, so you can check a detail without growing context.

Use Subagents for investigation

💡 Tip: Delegate research with "use subagents to investigate X". They explore in a separate context, keeping your main conversation clean for implementation.

Since context is your fundamental constraint, Subagents are one of the most powerful tools available. When CSC researches a codebase it reads lots of files, all of which consume your context. Subagents run in separate context windows and report back summaries:

Use subagents to investigate how our authentication system handles token
refresh, and whether we have any existing OAuth utilities I should reuse.

The Subagent explores the codebase, reads relevant files, and reports back with findings, all without cluttering your main conversation.

You can also use Subagents for verification after CSC implements something:

use a subagent to review this code for edge cases

Rewind with checkpoints

💡 Tip: Every action CSC makes creates a checkpoint. You can restore conversation, code, or both to any previous checkpoint.

CSC automatically checkpoints before changes. Double-tap Escape or run /rewind to open the rewind menu. You can restore conversation only, restore code only, restore both, or summarize from a selected message. See Checkpointing for details.

Instead of carefully planning every move, you can tell CSC to try something risky. If it doesn't work, rewind and try a different approach. Checkpoints persist across sessions, so you can close your terminal and still rewind later.

⚠️ Warning: Checkpoints only track changes made by CSC, not external processes. This isn't a replacement for git.

Resume conversations

💡 Tip: Run csc --continue to pick up where you left off, or --resume to choose from recent sessions.

CSC saves conversations locally. When a task spans multiple sessions, you don't have to re-explain the context:

csc --continue    # Resume the most recent conversation
csc --resume      # Select from recent conversations

Use /rename to give sessions descriptive names like "oauth-migration" or "debugging-memory-leak" so you can find them later. Treat sessions like branches: different workstreams can have separate, persistent contexts.

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Automate and scale

Once you're effective with one CSC, multiply your output with parallel sessions, non-interactive mode, and fan-out patterns.

Everything so far assumes one human, one CSC, and one conversation. But CSC scales horizontally. The techniques in this section show how you can get more done.

Run non-interactive mode

💡 Tip: Use csc -p "prompt" in CI, pre-commit hooks, or scripts. Add --output-format stream-json for streaming JSON output.

With csc -p "your prompt", you can run CSC non-interactively, without a session. Non-interactive mode is how you integrate CSC into CI pipelines, pre-commit hooks, or any automated workflow. The output formats let you parse results programmatically: plain text, JSON, or streaming JSON.

# One-off queries
csc -p "Explain what this project does"

# Structured output for scripts
csc -p "List all API endpoints" --output-format json

# Streaming for real-time processing
csc -p "Analyze this log file" --output-format stream-json

Run multiple CSC sessions

💡 Tip: Run multiple CSC sessions in parallel to speed up development, run isolated experiments, or start complex workflows.

There are three main ways to run parallel sessions:

• CSC desktop app: Manage multiple local sessions visually. Each session gets its own isolated worktree.
• CSC on the web: Run on CoStrict's secure cloud infrastructure in isolated VMs.
• Agent teams: Automated coordination of multiple sessions with shared tasks, messaging, and a team lead.

Beyond parallelizing work, multiple sessions enable quality-focused workflows. A fresh context improves code review since CSC won't be biased toward code it just wrote.

For example, use a Writer/Reviewer pattern:

Session A (Writer)	Session B (Reviewer)
Implement a rate limiter for our API endpoints
	Review the rate limiter implementation in @src/middleware/rateLimiter.ts. Look for edge cases, race conditions, and consistency with our existing middleware patterns.
Here's the review feedback: [Session B output]. Address these issues.

You can do something similar with tests: have one CSC write tests, then another write code to pass them.

Fan out across files

💡 Tip: Loop through tasks calling csc -p for each. Use --allowedTools to scope permissions for batch operations.

For large migrations or analyses, you can distribute work across many parallel CSC invocations:

Generate a task list

Have CSC list all files that need migrating (e.g., list all 2,000 Python files that need migrating)

Write a script to loop through the list

for file in $(cat files.txt); do
  csc -p "Migrate $file from React to Vue. Return OK or FAIL." \
    --allowedTools "Edit,Bash(git commit *)"
done

Test on a few files, then run at scale

Refine your prompt based on what goes wrong with the first 2-3 files, then run on the full set. The --allowedTools flag restricts what CSC can do, which matters when you're running unattended.

You can also integrate CSC into existing data/processing pipelines:

csc -p "<your prompt>" --output-format json | your_command

Use --verbose for debugging during development, and turn it off in production.

Run autonomously with auto mode

For uninterrupted execution with background safety checks, use auto mode. A classifier model reviews commands before they run, blocking scope escalation, unknown infrastructure, and hostile-content-driven actions while letting routine work proceed without prompts.

csc --permission-mode auto -p "fix all lint errors"

For non-interactive runs with the -p flag, auto mode aborts if the classifier repeatedly blocks actions, since there is no user to fall back to. See when auto mode falls back for thresholds.

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Avoid common failure patterns

These are common mistakes. Recognizing them early saves time:

• The kitchen sink session. You start with one task, then ask CSC something unrelated, then go back to the first task. Context is full of irrelevant information.

  Fix: /clear between unrelated tasks.

• Correcting over and over. CSC does something wrong, you correct it, it's still wrong, you correct again. Context is polluted with failed approaches.

  Fix: After two failed corrections, /clear and write a better initial prompt incorporating what you learned.

• The over-specified AGENTS.md. If your AGENTS.md is too long, CSC ignores half of it because important rules get lost in the noise.

  Fix: Ruthlessly prune. If CSC already does something correctly without the instruction, delete it or convert it to a hook.

• The trust-then-verify gap. CSC produces a plausible-looking implementation that doesn't handle edge cases.

  Fix: Always provide verification (tests, scripts, screenshots). If you can't verify it, don't ship it.

• The infinite exploration. You ask CSC to "investigate" something without scoping it. CSC reads hundreds of files, filling the context.

  Fix: Scope investigations narrowly or use Subagents so the exploration doesn't consume your main context.

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Develop your intuition

The patterns in this guide aren't set in stone. They're starting points that work well in general, but might not be optimal for every situation.

Sometimes you should let context accumulate because you're deep in one complex problem and the history is valuable. Sometimes you should skip planning and let CSC figure it out because the task is exploratory. Sometimes a vague prompt is exactly right because you want to see how CSC interprets the problem before constraining it.

Pay attention to what works. When CSC produces great output, notice what you did: the prompt structure, the context you provided, the mode you were in. When CSC struggles, ask why. Was the context too noisy? The prompt too vague? The task too big for one pass?

Over time, you'll develop intuition that no guide can capture. You'll know when to be specific and when to be open-ended, when to plan and when to explore, when to clear context and when to let it accumulate.