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Give an AI coding agent a compact map of your repository, clear task boundaries, and a definition of done—then let focused search retrieve the files and symbols it needs. Do not paste the entire codebase into the prompt. A short, scoped instruction file, sensible exclusions, limited tools, and two-step retrieval usually provide better grounding with less noise.
This approach works because an agent reasons only over the conversation, workspace content, instructions, references, and tool output currently available to it. The goal is not maximum context; it is the smallest set of authoritative context that explains the change and its constraints.
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What repository context does an AI coding agent actually need?
An agent needs enough information to understand the requested change, locate the responsible code, follow local conventions, and verify the result. It rarely needs every file. Context is assembled from the conversation, workspace files, instruction documents, references, and tool results, so irrelevant material competes with the details that determine a correct edit.
Start with the task contract
State four things before asking for code changes:
- Desired change: describe the behavior or defect in concrete terms.
- Constraints: identify supported runtimes, public APIs, compatibility rules, security requirements, and files that must not change.
- Acceptance checks: list tests, commands, screenshots, or observable behavior that proves the work.
- Stopping condition: define when the agent should stop investigating or editing.
For example, “Add pagination to the orders endpoint, preserve the existing response shape, add an integration test for an empty page, run the orders test suite, and do not change database migrations” is more useful than “Improve orders.” Clear task definitions and stopping conditions are recommended in GitHub’s guidance because they reduce retries and scope drift.
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Provide a map, not a code dump
The initial context should explain where the important pieces live: the application entry point, major modules, test locations, configuration, generated-code boundaries, and commands. The agent can then search for definitions and call sites instead of guessing from a pasted snapshot.
What should go in AGENTS.md or another project-instructions file?
Put stable, non-obvious repository knowledge in a concise project map. An AGENTS.md, .github/copilot-instructions.md, or equivalent file should orient an agent without repeating ordinary code that it can infer by reading the relevant files.
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- Architecture: identify applications, libraries, services, and their ownership boundaries.
- Module responsibilities: explain what each major directory does and where shared interfaces are defined.
- Entry points: name the commands or files used to start, build, lint, and test the project.
- Test conventions: state where unit, integration, end-to-end, and fixture tests belong.
- Dependency rules: document allowed directions, layering constraints, and public versus internal packages.
- Generated artifacts: identify files that are produced by a generator and the command that regenerates them.
- Non-obvious rules: record naming, error-handling, migration, localization, or security conventions that are easy to miss.
Leave out information the code already makes obvious
Do not copy entire API definitions, long tutorials, or every command-line option into the instruction file. Duplicated guidance becomes stale and consumes context on every task. Link or point to the authoritative file path when a detail is too large to summarize, then let the agent retrieve it only when needed.
Example project map
# Repository map
## Layout
- apps/web: browser application
- services/orders: orders API and domain logic
- packages/db: database client and migrations
- tests/e2e: end-to-end tests
## Commands
- pnpm install
- pnpm lint
- pnpm test --filter orders
- pnpm test:e2e
## Rules
- Keep HTTP handlers thin; business logic belongs in services/orders/src/domain.
- Do not edit generated files under packages/db/generated.
- Add new API behavior tests under services/orders/test.
- Run the focused orders test command before the full suite.
## Done means
- Existing tests remain green.
- New behavior has a regression test.
- Public response types and documentation are updated when they change.The exact format is flexible. What matters is that the map is short, maintained, and written for an unfamiliar engineer or agent.
How do I scope instructions so unrelated rules do not leak into a task?
Apply instructions at the narrowest folder or language scope that still covers the files they govern. A frontend task should not inherit backend deployment rules, and generated-code guidance should not dominate a hand-written source directory.
Use layered instruction files
Keep repository-wide rules at the root, then add smaller files in substantial subprojects. A root file can describe architecture and universal commands; a service-level file can explain its API conventions; a frontend file can document component, accessibility, or styling rules. The agent should receive the instructions applicable to the path it is editing.
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State which rule wins when scopes overlap. For example, a service instruction can say that its local test command supplements the root test command, while a generated directory can say that generated output must be changed only through its generator. Explicit precedence prevents an agent from treating every instruction as equally applicable.
Review instruction files like code
Remove obsolete commands, renamed directories, and rules that no longer match the implementation. A stale project map is worse than a short one because it sends retrieval toward the wrong files with high confidence.
How can semantic or symbol-aware search reduce prompt size?
Use search to retrieve relevant snippets, definitions, and call sites instead of attaching the whole workspace. Semantic indexing is designed to find relevant sections without preloading every file on each request, while symbol-aware search can jump directly to a class, function, route, or interface.
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Search in an expanding sequence
- Search the project map and task terms. Look for the feature name, route, error code, class, or configuration key mentioned in the request.
- Inspect definitions. Open the implementation of the matching function, type, component, or command.
- Inspect call sites. Find where the symbol is used so changes preserve contracts and side effects.
- Inspect adjacent tests. Read the nearest unit or integration tests to learn expected behavior and fixtures.
- Expand only for ambiguity. Fetch a full document, configuration file, or dependency implementation when the focused snippets leave an unresolved question.
This sequence follows the two-step retrieval pattern described by Google for Developers: begin with a document search operation, then obtain the larger source only when the result requires it.
Search by behavior as well as filename
Filename searches miss code hidden behind generic names. Combine text terms, symbols, routes, event names, database columns, and error messages. If a task changes authentication, search for the permission check, middleware registration, token parser, and tests—not just files named auth.
Preserve dependency context
When a snippet depends on a type or helper, retrieve that definition and its contract. A tiny isolated function can look correct while violating an interface, transaction boundary, or serialization rule elsewhere.
Which files and outputs should be excluded from retrieval?
Exclude material that is generated, repetitive, huge, or unlikely to inform the change. Narrowing the search space improves relevance and leaves room for the code and tests that matter.
Common exclusion candidates
- Build and coverage output such as
dist,build,out, and coverage reports. - Generated clients, schemas, snapshots, lockfile derivatives, and compiled assets when they are not the source of truth.
- Vendored dependencies and package-manager caches.
- Logs, crash dumps, temporary files, editor metadata, and local environment directories.
- Large fixtures or recordings that are not relevant to the requested behavior.
- Binary assets and minified bundles that cannot provide useful source-level context.
Keep an exclusion from hiding the authoritative input. If a generated client is excluded, expose the schema or generator configuration that defines it. If logs are excluded globally, attach the small incident excerpt that explains the bug when it is genuinely needed.
Use allowlists for sensitive work
For security-sensitive or regulated repositories, start with an allowlist of approved roots and expand it deliberately. This reduces accidental exposure of secrets, personal data, and unrelated products. Never place credentials, private keys, or production dumps in an instruction file or prompt.
How many tools should an agent have enabled?
Enable the smallest tool set that can complete the task. A focused set of repository search, file editing, test execution, and—when required—browser or documentation tools makes tool selection more relevant and reduces context overhead.
Match tools to the task
| Task type | Useful tools | Usually unnecessary at first |
|---|---|---|
| Local refactor | Symbol search, file read/write, formatter, focused tests | Browser automation, deployment controls |
| API integration | Repository search, schema/docs lookup, test runner, request fixture tools | Unrelated infrastructure consoles |
| UI behavior change | Component search, browser or screenshot tool, unit and end-to-end tests | Database administration tools |
| Build or release fix | Configuration search, command runner, CI logs, package metadata | Broad application-editing tools before the failure is localized |
Tool restrictions are not a substitute for permissions. Keep repository access, secret handling, and destructive-command policies enforced outside the prompt.
How should I handle a monorepo or multi-service workspace?
Give the agent explicit repository boundaries. Multi-root workspaces or clearly named service and folder roots prevent a task in one product from pulling in unrelated applications, tests, and infrastructure.
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Define ownership and dependency direction
Document which team or service owns a directory, which packages are public, and which dependencies are allowed. If a billing service may consume a shared type but must not import a web application, say so in the local map. This lets the agent distinguish a valid cross-file dependency from an accidental shortcut.
Split work into focused subtasks
For a cross-cutting change, separate discovery, implementation, migration, and verification when they involve different boundaries. Each session can receive the map and constraints for its own area, then a final review can inspect the combined diff and integration points. This is safer than giving one session every service and asking it to keep all interactions in memory.
Attach an interface contract for cross-service edits
When a change crosses a service boundary, provide the request and response schema, compatibility requirement, rollout order, and owner of the contract. Retrieve implementations on both sides only after the contract is understood.
What is the two-step retrieval method, and when should I fetch a whole file?
Two-step retrieval means searching for focused snippets first and fetching complete documents only when those snippets leave an ambiguity. It balances precision and coverage without treating every file as equally relevant.
Step one: retrieve narrow evidence
Start with the project map, matching symbols, nearby tests, and the configuration that directly controls the behavior. Ask the agent to explain why each result is relevant before expanding the context. This creates a traceable set of files rather than an unexamined pile.
Step two: expand deliberately
Fetch a whole file when control flow spans distant sections, a class relies on constructor state, a configuration file has inherited defaults, or a document defines a contract that snippets omit. Keep the expansion tied to a specific question: “Where is this value transformed?” is actionable; “Read everything” is not.
Stop when the evidence closes the question
Once the agent can identify the edit, its dependencies, and its verification, stop retrieving. More context can introduce conflicting examples, obsolete code paths, or unrelated conventions.
How do I prevent a long session from becoming less reliable?
Start a new session for unrelated work, compact long histories, and keep stable instructions early in the conversation. Session growth can bury the task contract beneath tool output and intermediate guesses.
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Separate unrelated objectives
Do not combine a dependency upgrade, UI redesign, and production incident investigation in one thread. Each objective has different relevant files, tests, and stopping conditions. A fresh session gives retrieval a clean relevance signal.
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Summarize before compaction
When a session must continue, record the current plan, files changed, tests run, unresolved questions, and constraints in a short handoff. Preserve exact error messages and command results, but omit exploratory output that no longer affects the decision.
Keep stable guidance cache-friendly
Place durable repository instructions near the beginning and avoid rewriting them for every task. Where the platform supports prompt caching, stable early content can be reused while task-specific details change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which context strategy should I choose?
The right strategy depends on repository size, dependency spread, and how much uncertainty the task contains. Compare approaches by precision, coverage, token cost and latency, maintenance, and isolation.
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|---|---|---|---|---|---|
| Paste the whole repository | Low when noise is high | Potentially broad, but hard to reason over | High and often impractical | None, but every prompt is large | Rare emergency inspection of a very small project |
| One large instruction file | Moderate if carefully maintained | Good orientation, weak for implementation details | Repeated context overhead | High risk of stale or conflicting rules | Small repositories with few boundaries |
| Scoped maps plus semantic search | High for focused tasks | Expands across dependencies when needed | Lower initial cost; incremental retrieval | Requires maintained maps and indexes | Most medium and large repositories |
| Separate sessions by service | High within each boundary | Needs an explicit integration handoff | Lower per-session growth, more coordination | Requires clear ownership and contracts | Monorepos and cross-service work |
No authoritative source establishes a universal ideal context size. Treat context volume as task-dependent: a broad architectural change needs more coverage than a one-function bug fix, but both benefit from excluding irrelevant material.
What should I do when the agent still gets lost?
Diagnose the failure by symptom, then change the context rather than simply adding more files.
The agent edits the wrong module
Add the ownership boundary and the canonical entry point to the project map. Search for the public symbol or route, inspect its call sites, and explicitly name files that are similar but out of scope.
The agent repeats failed approaches
Write the acceptance check and stopping condition in the task. Preserve the exact failing command and output, then ask for a small diagnosis before another edit. A new session may be preferable if the history is dominated by abandoned attempts.
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The agent misses a dependency
Retrieve the symbol definition, interface, and callers together. In a monorepo, provide the package boundary and dependency direction so the agent knows where a compatible change belongs.
The agent changes generated output directly
Mark generated paths as read-only in the instructions and name the generator command. Ask the agent to modify the source schema or template, regenerate the artifact, and verify that the diff contains only expected output.
The agent is distracted by logs or fixtures
Exclude noisy paths and attach only the relevant excerpt or fixture. If the fixture is authoritative for a regression, state that explicitly so exclusion rules do not hide it.
What is a practical end-to-end workflow?
Use this sequence whenever you begin a repository task.
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- Write the task contract. State the requested behavior, constraints, acceptance checks, and stopping condition.
- Read the applicable instruction files. Start at the repository root, then apply files governing the target folder or language.
- Identify the boundary. Select the application, service, package, or workspace root that owns the change.
- Search narrowly. Find the relevant route, symbol, configuration key, error, and nearby tests.
- Inspect dependencies. Retrieve definitions and call sites for symbols that cross files or package boundaries.
- Exclude noise. Omit generated output, builds, vendored code, logs, and unrelated fixtures unless a specific question requires them.
- Enable only needed tools. Add browser, documentation, infrastructure, or deployment tools only when the task calls for them.
- Implement in a focused session. Keep unrelated cleanup out of the diff.
- Verify at the smallest useful scope. Run the focused formatter, linter, and tests first, then broader checks required by the project map.
- Review the diff against the contract. Confirm that the change, tests, generated artifacts, and stopping condition all match the original request.
What should I check before handing work to an AI coding agent?
- The task names a concrete outcome rather than a vague goal.
- A maintained project map identifies architecture, commands, tests, and boundaries.
- Instructions are scoped to the folders and languages they govern.
- Generated, vendored, temporary, and sensitive paths are excluded or explicitly controlled.
- The agent can search symbols and text instead of receiving a repository dump.
- Tool access matches the task and excludes unnecessary capabilities.
- Cross-service work has an interface contract and ownership information.
- Retrieval starts with snippets and expands only to resolve a known ambiguity.
- The session has a stopping condition and a verification command.
The most reliable pattern is simple: map the repository, state the task precisely, retrieve evidence incrementally, and stop when the acceptance checks are satisfied. Grounding should narrow the search space, not preload every available source, as Microsoft’s Visual Studio Code guidance puts it.
Frequently Asked Questions
How long should an AGENTS.md file be?
There is no fixed word or token limit. Keep it to durable rules an unfamiliar contributor could not infer quickly, and move detailed procedures into the files or documentation that own them. If the file becomes a catalog of every command and exception, split it by folder or language.
Should I give the agent the entire Git history?
Usually not. Provide a specific commit, issue, or migration note when historical intent answers a current ambiguity, rather than attaching an unfiltered history. The current implementation and its tests should remain the primary evidence.
How can I protect secrets while providing useful context?
Use repository and tool permissions to prevent access to secret stores, environment dumps, and production data. Redact credentials from logs and examples, and provide schemas, variable names, or sanitized samples instead of secret values.
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When is full-file retrieval better than snippet retrieval?
Use the whole file when behavior depends on distant declarations, inherited configuration, class-level state, or ordering that snippets hide. Keep the reason explicit, then return to focused retrieval once that dependency is understood.
Can separate agent sessions safely work on one feature?
Yes, if each session has a defined boundary and produces a concise handoff containing changed files, interface assumptions, tests, and unresolved risks. A final integration review should inspect the combined diff and run checks that cover the shared contract.
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