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feature-tracking

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Maintain durable feature-level memory across AI coding sessions with lightweight Markdown tracks for status, source-of-truth docs, decisions, risks, and changes.

When to use

• Use when starting or resuming work on a feature after a session, agent, or tool change.
• Use when feature knowledge is scattered across PRDs, API notes, plans, issues, and old commits.
• Use when a long-lived feature needs durable decisions, risks, rollout constraints, or migration notes.
• Use when reviewing or finishing feature work and recording the verified outcome for future agents.
• Use when adopting lightweight project memory in an existing repository without reorganizing all documentation.

When not to use

• Feature Tracking does not replace source code, tests, issue trackers, product specifications, or architecture records.
• It depends on agents and contributors keeping tracks current; stale summaries can mislead future work.
• Markdown link checks cannot establish that the linked content is factually current.
• The workflow does not automatically resolve conflicts between code, tests, and documentation; discrepancies must be investigated.
• Large repositories may need ownership rules or automation beyond this lightweight workflow.
• Repository-specific validation commands and status vocabularies must be discovered rather than assumed.

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