Explicit retrospective of a coding session with evidence-backed suggestions for future work.
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Review the current coding session by default. Review another session only when the user specifies it and the evidence is accessible. Use the available writing-for-agents guidance when suggesting agent instructions.
Reviewers may need to inspect code and history to understand a change; do not assume a diff is enough. Treat mechanical checks, rules, and documentation as options whose costs must be justified by the observed failure.
This is a read-only suggestion workflow. Present proposed changes in chat; edit AGENTS.md, code, CI, memory, or issues, send messages, and start background tasks only when separately authorized. Existing explicit authorization remains effective.
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Read public X/Twitter post URLs as structured evidence through the ADHX API. Use for relevant user-provided or research-discovered x.com, twitter.com, or adhx.com links. ADHX does not search X, and long-form Article content may be incomplete.
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Design, review, or report a measured performance comparison. Use for benchmark methodology, speedup or regression claims, and performance-based choices; not generic performance discussion, ordinary dependency bumps, local renames, or prose edits.
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Trace what an actual code change could break beyond its diff when interfaces, serialized data, database schemas, configuration, caches, lifecycle ordering, or cross-language consumers are involved. Use for explicit impact analysis; not local renames, prose edits, ordinary dependency bumps, or generic architecture discussion.
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Shared vocabulary for designing deep modules, interfaces, seams, adapters, leverage, and locality. Use when designing or reshaping module boundaries, making code more testable, or evaluating interface depth.
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Plan or implement retirement of a system, API, feature, persisted configuration, or database shape. Use for compatibility cutovers, explicit deprecation review, or an explicit unreleased replacement decision, including determining whether consumers or data exist; not ordinary dependency bumps, local renames, prose edits, or generic architecture discussion.
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Disciplined diagnosis loop for hard bugs, regressions, flaky failures, and performance problems with unclear cause. Use for root-cause debugging after a concrete symptom exists; do not use for routine implementation or speculative cleanup.
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