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Numbers (stage counts, phase rollup, duration) come from\n  `aidlc-runtime.ts summary`; prose comes from the audit trail and\n  artefacts. Renders to the terminal only — writes no file, never\n  mutates workflow state, never emits audit events.\nargument-hint: \"\"\nuser-invocable: true\nclassification: read-only\n---\n\n# AI-DLC Session Replay\n\n## Purpose\n\nTurn a workflow's audit trail and artefacts into a readable story: what\nwas decided, in what order, and why. For async review, for stakeholders\nwho weren't present, or as a post-session record. Not a raw log dump.\n\n## Classification\n\nRead-only. This skill renders the narrative to the terminal and writes\n**no file**. It never advances the workflow stage pointer and never\nemits an audit event.\n\n## The counting rule\n\nAll counts and aggregates — number of stages, per-phase breakdown,\nduration, approved\u002Ffailed\u002Fpending tallies, learnings captured — come\nfrom the tool, not from eyeballing files:\n\n```bash\nbun {{HARNESS_DIR}}\u002Ftools\u002Faidlc-runtime.ts summary --json\n```\n\nThe narrative prose (what happened, key decisions, reasoning) is yours\nto synthesise from the active record's audit shards and artefacts. The\nskeleton numbers are the tool's. Never hand-count stages or artefacts\nwhen the tool already reports the figure.\n\n## Steps\n\n### Step 1: Read the aggregates\n\nRun `bun {{HARNESS_DIR}}\u002Ftools\u002Faidlc-runtime.ts summary --json`.\n\nIf it exits non-zero (no `runtime-graph.json` yet), print:\n\n```\nNo session data yet — start a workflow with \u002Faidlc before running\n\u002Faidlc-replay.\n```\n\nand STOP. Otherwise keep the parsed JSON; you'll cite its fields for\nevery number in the report.\n\n### Step 2: Read the narrative sources\n\nResolve `\u003Cactive-space>` from `aidlc\u002Factive-space` (default `default`) and\n`\u003Cactive-intent>` from\n`aidlc\u002Fspaces\u002F\u003Cactive-space>\u002Fintents\u002Factive-intent`. The active workflow\nrecord is\n`aidlc\u002Fspaces\u002F\u003Cactive-space>\u002Fintents\u002F\u003Cactive-intent>`.\n\n- Every `.md` shard under `\u003Crecord>\u002Faudit\u002F` — the full event trail; order\n  events by their `Timestamp` fields for the narrative.\n- `\u003Crecord>\u002Faidlc-state.md` — the active-stage cursor.\n- The artefacts recursively under `\u003Crecord>\u002F\u003Cphase>\u002F` — what each stage\n  produced, including per-unit Construction outputs.\n\nThese are your sources for *prose*. Do not derive counts from them when\nStep 1's JSON already carries the count.\n\n### Step 3: Render the replay\n\nPrint the narrative to the terminal in this shape (write no file):\n\n```markdown\n# Session Replay\n**Workflow**: {summary.workflow_id}\n**Scope**: {summary.scope}\n**Duration**: {summary.duration_minutes} min   (or \"in progress\")\n**Stages**: {summary.stages.approved} approved \u002F {summary.stages.total} total\n\n## Executive Summary\n{3-5 sentences: what was built or decided, key choices, constraints, outcome}\n\n## Timeline\n{For each phase in summary.by_phase, in workflow order:}\n\n### {Phase} Phase  —  {by_phase[phase].approved}\u002F{by_phase[phase].total} stages approved\n\n#### {Stage Name}\n**What happened**: {1-2 sentences from the audit trail}\n**Key decisions**: {bullets, with reasoning drawn from the audit shards}\n**Artefacts produced**: {list with one-line descriptions}\n\n{...repeat per stage that executed...}\n\n## Decisions Register Summary\n{Table: decision | alternatives considered | chosen option | rationale}\n\n## Learnings Captured\nFrom orchestrator: {summary.learnings.from_orchestrator}\nFrom user additions: {summary.learnings.from_user_addition}\n{Then narrate the notable ones from the stage memory.md diaries.}\n\n## What's Next\n{Outstanding open threads from the last audit entries \u002F open questions}\n```\n\n### Step 4: Offer adjustments\n\nYou may offer: \"Want a different tone (more technical \u002F more executive)\nor an added section?\" — re-render to the terminal if asked. Do not loop\non it; one offer is enough. If the user wants the replay saved, point\nthem at `\u002Faidlc-outcomes-pack` (the skill that writes a file) rather\nthan writing one here.\n",{"data":38,"body":42},{"name":4,"description":6,"argument-hint":39,"user-invocable":40,"classification":41},"",true,"read-only",{"type":43,"children":44},"root",[45,54,61,67,73,86,92,97,136,141,147,154,167,180,190,195,201,253,311,324,330,335,784,790,803],{"type":46,"tag":47,"props":48,"children":50},"element","h1",{"id":49},"ai-dlc-session-replay",[51],{"type":52,"value":53},"text","AI-DLC Session Replay",{"type":46,"tag":55,"props":56,"children":58},"h2",{"id":57},"purpose",[59],{"type":52,"value":60},"Purpose",{"type":46,"tag":62,"props":63,"children":64},"p",{},[65],{"type":52,"value":66},"Turn a workflow's audit trail and artefacts into a readable story: what\nwas decided, in what order, and why. For async review, for stakeholders\nwho weren't present, or as a post-session record. 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Do not derive counts from them when\nStep 1's JSON already carries the count.",{"type":46,"tag":148,"props":325,"children":327},{"id":326},"step-3-render-the-replay",[328],{"type":52,"value":329},"Step 3: Render the replay",{"type":46,"tag":62,"props":331,"children":332},{},[333],{"type":52,"value":334},"Print the narrative to the terminal in this shape (write no file):",{"type":46,"tag":98,"props":336,"children":340},{"className":337,"code":338,"language":339,"meta":39,"style":39},"language-markdown shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","# Session Replay\n**Workflow**: {summary.workflow_id}\n**Scope**: {summary.scope}\n**Duration**: {summary.duration_minutes} min   (or \"in progress\")\n**Stages**: {summary.stages.approved} approved \u002F {summary.stages.total} total\n\n## Executive Summary\n{3-5 sentences: what was built or decided, key choices, constraints, outcome}\n\n## Timeline\n{For each phase in summary.by_phase, in workflow 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