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To keep Claude Code focused without stripping away useful project context, put the right information in the right place: state the deliverable and constraints in your current prompt, keep lasting conventions in project or personal memory, add only relevant files, and connect external tools only when the task needs them. Then check the result against explicit acceptance criteria. These controls work at different scopes; some also determine what Claude Code can access or do, not just how it phrases an answer.
What progressive disclosure means in Claude Code
Progressive disclosure is a practical way to provide Claude Code with information in layers rather than putting every preference, project detail, and possible instruction into one request. Start with the task and its required result. Add persistent guidance for rules that should apply again. Supply specific context and integrations only when they help with the current work.
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This is an editorial approach, not a named Anthropic feature or a guarantee of a particular response. Anthropic’s prompting guidance recommends specifying the output format and constraints, providing relevant examples, and explaining context or motivation. Those practices can make the request clearer, but they do not ensure a particular result: Anthropic’s prompting guidance.
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Start with a concrete request
For the current task, spell out what Claude Code should accomplish, what it should not do, and what a satisfactory deliverable looks like. A useful prompt makes the intended scope and response format clear before adding background.
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- Task: Name the outcome, such as fixing a specific failing test or explaining a function.
- Scope: Identify files or components to include or exclude, when known.
- Constraints: State requirements such as preserving public APIs, avoiding unrelated edits, or not installing dependencies.
- Format: Request the form that will be useful: a concise explanation, a patch, a checklist, or another specific deliverable.
- Acceptance criteria: Describe how to tell whether the work is complete, such as tests passing or a particular behavior being preserved.
For example: “Find why the login test fails. Inspect the authentication code and relevant test; do not change unrelated files or add dependencies. Make the smallest fix, run the relevant test, and report the cause, changed files, and test result.” The example is a prompt pattern, not a promise that Claude Code will always follow it perfectly.
Put durable guidance in the right memory scope
Instructions that should persist belong outside a one-off request. Anthropic’s surfaced memory documentation distinguishes project guidance intended for the team from personal preferences. Its documented roles are project CLAUDE.md for shared project instructions and ~/.claude/CLAUDE.md for user preferences. The page available for those details was an older Chinese-language version, so check current English documentation before relying on exact syntax or behavior: Anthropic’s memory guide.
Project guidance
Use project memory for conventions that contributors should share: architectural boundaries, repository-specific commands, testing expectations, or rules about generated files. Keep it focused on durable facts. A request-specific instruction—such as changing one function today—usually belongs in that request instead.
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Personal preferences
Use personal memory for preferences that apply to your work across projects, rather than rules that teammates must follow. Separating personal defaults from team instructions reduces the chance that a private preference is mistaken for a project requirement.
Add only task-relevant context
Claude Code operates in a terminal and can explore project code as needed, according to Anthropic’s common-tasks documentation: Anthropic’s common tasks guide. Still, name the files, behavior, or background that matters when that context is not obvious. This helps distinguish the relevant path from unrelated parts of a repository.
For a code change, point to the failing test or expected behavior. For an explanation, identify the component and the reader’s level of familiarity. For a long task, Anthropic’s prompting guidance discusses saving state or context externally and using verification tools. Treat those as ways to organize work—not as guarantees that context will be preserved or output will improve.
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Choose CLI controls for access and interaction
Claude Code’s command-line options can shape more than prose. The CLI reference documents controls for working directories, allowed and disallowed tools, print and output formats, turn limits, model selection, and permission mode: Anthropic’s CLI reference. Choose these based on what the task requires; directory access and tool permissions can affect what Claude Code reaches or does.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problems- Working directories: Define which project locations are in scope.
- Tool allow/deny controls: Restrict or enable tool use for the invocation.
- Print and output formats: Control how output is returned in supported modes; they do not replace a clear request about content.
- Turn limits: Bound the interaction length, which can constrain how much work fits in a run.
- Model selection: Select a model through the documented option when appropriate.
- Permission mode: Set the interaction and approval behavior for actions.
These are not interchangeable style settings. A format option affects output representation; a directory or permission setting can change access and action. The CLI reference is the source for current option names and usage, so consult it rather than relying on remembered syntax.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Connect MCP only when an external source or action is needed
The Model Context Protocol (MCP) is an open protocol for standardizing how applications provide context to language models. In Claude Code, MCP can connect to external tools and data sources; it is useful when a task needs information or an action outside the local project. See Anthropic’s MCP overview.
Consider the integration’s scope and permissions before enabling it. Anthropic’s Claude Code MCP guide notes that project-scoped configuration can involve approval, and that MCP output can affect context use: Anthropic’s Claude Code MCP guide. Because the surfaced guide was translated, consult the current English documentation for exact configuration and approval behavior. Add an integration when its data or action is needed, not simply to provide more possible context.
Check the result against the request
Before accepting a response or change, compare it with the criteria you stated. For code work, inspect the diff and the relevant test result; for an explanation, check that it answers the requested question at the requested level and format. If something is missing, give a targeted correction—such as naming the unmet criterion—instead of repeating all the project background.
- Does the result address the requested outcome?
- Did it stay within the stated scope and constraints?
- Is the requested format usable?
- Were relevant checks or tests run, and are their results reported accurately?
- Did any tool or integration access exceed what the task needed?
Which control should you use?
| Control | Persistence and scope | What it shapes | Use it for |
|---|---|---|---|
| Immediate prompt | Current request | Deliverable, constraints, context, and response format | Task-specific instructions and acceptance criteria |
| Project memory | Project; intended for shared guidance | Durable team conventions | Repository rules and recurring project practices |
| Personal memory | User; intended for personal preferences | Preferences across work | Defaults that should not be imposed as team policy |
| CLI options | Invocation-level controls | Directories, tools, output mode, turns, model, and permissions | Controlling access and interaction behavior |
| MCP integration | Configured connection and scope | External data sources and tools | Tasks that require outside information or actions |
The prompt and memory distinguish one-request instructions from persistent guidance; project and personal memory distinguish shared scope from personal scope; local files and MCP distinguish context sources; and CLI permissions and output options distinguish access from presentation. Use the narrowest control that fits the need.
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