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How to Audit Hidden Reminders and Context Usage in Claude Code Logs

Михаил 2026年08月01日 17:10 0 次阅读 来源:Dev.to

How to Audit Hidden Reminders and Context Usage in Claude Code Logs | Agent Lab Journal Agent Lab Journal Guides Glossary Advanced field guide How to Audit Hidden Reminders and Context Usage in Claude Code Logs Advanced · 45 min read · Local analysis · Updated August 1, 2026 The visible transcript in Claude Code is not necessarily a complete representation of everything recorded around a request. Service messages, internal reminder markers, tool payloads, and usage metadata can exist in session logs without appearing as ordinary chat turns. If you want to know how often ip_reminder occurs—or how input, output, cache creation, and cache read tokens are distributed—you need to inspect the stored records directly and preserve enough structure to avoid misleading totals. In this guide What this audit can establish Concrete investigation case Locate and select one session Preserve an auditable copy Run a quick structural check Build the full local report Interpret reminder and token data Verify the report independently Failure cases and repairs Limitations What this audit can—and cannot—establish This workflow examines one local session stored as JSON Lines (JSONL): a text format in which each line is normally an independent JSON value. It creates a report with: the selected file’s path, size, modification time, and SHA-256 digest; the number of physical lines, parsed records, blank lines, and malformed lines; every record containing the exact, case-sensitive string ip_reminder; the JSON paths at which the marker was found; timestamps and record types when those fields are available; per-record and aggregate input, output, cache creation, and cache read token values; a chronological CSV suitable for a spreadsheet or notebook; a machine-readable JSON report for later comparison. The report shows what is present in the selected file. It does not prove why a reminder was inserted, whether it was transmitted to a model exactly as stored, or how the client’s undocumented inte

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