Keep Coding Agent Context Files Small

Coding agents need repository context, but they do not need the entire team handbook in every session. Large instruction files compete with code, tool output, and conversation history for attention. They also become harder to maintain. The goal is a small, reliable entry point that tells an agent how to work and where to look next.

§ Step 1: Start with the agent’s actual entry point

Identify which instruction files your tools discover. Claude Code uses CLAUDE.md, Codex supports AGENTS.md, and Gemini CLI uses GEMINI.md by default. Discovery, nesting, and override behavior differ between tools, so check the documentation for the version you run. Do not assume that creating one file makes every agent read it.

If your team uses several agents, keep shared guidance in one maintained document and use small tool-specific entry points. Verify whether each tool supports importing that document. Otherwise, explicitly instruct the agent to read it. Avoid copying a large handbook into three files.

§ Step 2: Set a working size budget

Choose a modest budget for the root instructions, such as 400 to 600 words. This is a maintenance target, not a universal context-window limit. A smaller repository may need much less.

Include only facts that affect most tasks:

• Repository map: where application code, tests, and configuration live.
• Essential commands: the supported install, test, lint, and build commands.
• Hard constraints: generated files, security boundaries, and compatibility requirements.
• Completion checks: what to verify and what to report before handing work back.

Remove broad advice such as “write clean code.” Replace it with a repository-specific rule only when that rule changes a concrete decision.

§ Step 3: Separate instructions from reference material

An instruction tells the agent what to do. Reference material explains something it may need to understand. Keep the former in the entry point and move the latter into focused documents.

For example, replace a long authentication explanation with: “Before changing session handling, read docs/authentication.md. Preserve the existing cookie security settings.” This gives the agent a clear trigger, a location, and a constraint without loading the full design into every unrelated task.

Use explicit paths and meaningful filenames. A vague instruction to “read the docs” transfers the discovery problem to the agent.

§ Step 4: Scope details to the relevant directory

Frontend styling rules rarely belong in every backend task. Where your tool supports directory-scoped instructions, place specialized guidance near the code it governs. Keep the root file focused on repository-wide rules.

If scoped discovery is unavailable, add a short routing list instead:

• For database changes, read docs/database-changes.md.
• For public API changes, read docs/api-compatibility.md.
• For deployment work, read docs/release-process.md.

Avoid deep chains of references. The agent should reach the relevant instructions in one or two deliberate reads, not follow a documentation maze.

§ Step 5: Test the context with a real task

Start a fresh session and ask for a small, representative change. Check whether the agent finds the right files, uses the correct commands, and respects the important constraints. Where the tool exposes loaded instructions, inspect them rather than assuming discovery worked.

Vana API can keep the provider endpoint consistent while you work with Claude Code, Codex, or Gemini CLI. It supports OpenAI-compatible, Anthropic Messages, and Gemini native protocols at https://api.vanaapi.com. Instruction discovery still belongs to the agent tool, not the endpoint. Keep the tool, task, and model unchanged when comparing two instruction-file versions.

§ Step 6: Maintain context like code

Review context files whenever commands, directories, or policies change. Delete obsolete instructions instead of appending corrections beneath them. A simple CI check can flag broken reference paths and unexpected file growth; human review should resolve contradictions.

Measure success by fewer incorrect assumptions and less repeated steering, not just fewer words. Smaller instructions can reduce input-token usage when included in requests, but costs also depend on tool behavior, caching, and the rest of the session.

If you want to try this workflow across supported coding tools, create a Vana API account. Usage is billed per real token with no monthly fee. Keep the experiment narrow: one task, one concise context file, and a clear record of what improved.