Context Management & Reliability15% of the exam

Context management in large codebase exploration

How to keep long codebase explorations precise: spot context degradation, persist findings in scratchpad and state files, push verbose searches into subagents, seed each phase with a summary, recover crashed runs from manifests, compact with a focus and block generated code from reads.

Official exam objective
Manage context effectively in large codebase exploration

~8 min read · 8 practice questions ·

What the exam expects

  • Recognize context degradation in a long exploration session (inconsistent answers, "typical patterns" instead of the classes found earlier) and respond by persisting findings rather than by asking for more tokens.
  • Have agents keep scratchpad and per-item state files that each new context window reads first.
  • Delegate narrow, verbose investigations ("find all test files", "trace refund flow dependencies") to subagents while the main agent keeps the high-level plan.
  • Summarize one exploration phase and inject that summary into the prompts of the next phase's subagents.
  • Design crash recovery around structured state exports and a manifest the coordinator loads on resume.
  • Use /compact with focus instructions, know what survives compaction, and keep generated or vendored code out of reads.

Key terms: context degradation (precision loss as the window fills); scratchpad file (notes on disk the agent rereads); state manifest (a structured record of done and pending work in a known location); compaction (replacing the conversation with a summary); Read deny rule (a permissions.deny entry that blocks file reads).

Key facts

Degradation symptom
Detail
Inconsistent answers and "typical patterns" instead of discovered classes
Subagent summary size
Detail
Often 1,000-2,000 tokens after extensive exploration
What crosses into a non-fork subagent
Detail
Only the Agent tool's prompt string from the parent
State file format
Detail
JSON for status; freeform notes for progress; git for checkpoints
Compaction across windows
Detail
Not sufficient alone; does not always pass clear state
Survives compaction from disk
Detail
Project-root CLAUDE.md, unscoped rules, auto memory, plan-mode plan
Summarized away
Detail
paths: rules, nested CLAUDE.md, hook-added context
Files re-read after compaction
Detail
Up to five; a file over 5,000 tokens returns as a path reference
Team-wide read block
Detail
Read deny rules in committed .claude/settings.json
Sources for this section (7)
  • Why does a three-hour exploration session start describing "typical patterns" instead of named classes?
  • When should you run /compact with focus instructions instead of /clear?
  • Why is a JSON status file preferred over Markdown for per-item progress?
  • What is the only parent content a non-fork subagent receives?

The questions are free to read. Answers with their sources and self-grading are included with the pack.

Keep reading with the Claude Certified Architect - Foundations pack

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