pipeline
// End-to-end source processing -- seed, reduce, process all claims through reflect/reweave/verify, archive. The full pipeline in one command. Triggers on "/pipeline", "/pipeline [file]", "process this end to end", "full pipeline".
EXECUTE NOW
Target: $ARGUMENTS
Parse immediately:
- Source file path: the file to process (required)
--handoff: output RALPH HANDOFF block at end (for chaining)- If target is empty: list files in {DOMAIN:inbox}/ and ask which to process
Step 0: Read Vocabulary
Read ops/derivation-manifest.md (or fall back to ops/derivation.md) for domain vocabulary mapping. All output must use domain-native terms. If neither file exists, use universal terms.
START NOW. Run the full pipeline.
Pipeline Overview
The pipeline chains four phases. Each phase uses skill invocation or /ralph for subagent-based processing. State lives in the queue file — the pipeline is stateless orchestration on top of stateful queue entries.
Source file
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Phase 1: /seed — create extract task, move source to archive
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Phase 2: /reduce (via /ralph) — extract claims from source
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Phase 3: /ralph (all claims) — create -> reflect -> reweave -> verify
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Phase 4: /archive-batch — move task files, generate summary
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Complete
The pipeline is the convenience wrapper. /ralph is the engine. /seed is the entry point.
Phase 1: Seed
Invoke /seed on the target file to create the extract task, check for duplicates, and move the source to its archive folder.
How to invoke:
Use the Skill tool if available, otherwise execute the /seed workflow directly:
- Validate source exists
- Check for prior processing (duplicate detection)
- Create archive folder
- Move source from {DOMAIN:inbox} to archive
- Create extract task file
- Add extract task to queue
Capture from seed output:
- Batch ID: the source basename (used for --batch filtering in subsequent steps)
- Archive folder path: where the source was moved
- next_claim_start: the claim numbering start
Report: $ Seeded: {source-name}
If seed reports the file was already processed: Ask the user whether to proceed or skip. Do NOT auto-skip — the user may want to re-process with different scope.
Phase 2: Extract (Reduce)
Process the extract task via /ralph. This spawns a subagent that runs /reduce, extracting claims from the source and creating task entries in the queue.
How to invoke:
/ralph 1 --batch {batch_id} --type extract
Or via Task tool:
Task(
prompt = "Run /ralph 1 --batch {batch_id} --type extract",
description = "extract: {batch_id}"
)
After completion, read the queue to count extracted claims and enrichments:
Check how many pending tasks exist for this batch. The reduce phase creates 1 queue entry per claim and 1 per enrichment.
Report:
$ Extracted: {N} {DOMAIN:note_plural}, {M} enrichments
Processing {total_tasks} tasks through the pipeline...
If zero claims extracted: Report the issue. For TFT sources, zero extraction is a bug — the source almost certainly contains extractable content. Ask the user whether to retry with different scope or skip.
Phase 3: Process All Claims
Count total pending tasks for this batch from the queue. Then process all of them through the full phase sequence.
How to invoke:
/ralph {remaining_count} --batch {batch_id}
Or via Task tool:
Task(
prompt = "Run /ralph {remaining_count} --batch {batch_id}",
description = "process: {batch_id} ({remaining_count} tasks)"
)
This processes every claim through: create -> reflect -> reweave -> verify. And every enrichment through: enrich -> reflect -> reweave -> verify.
Each phase runs in an isolated subagent with fresh context. /ralph handles all the orchestration: subagent spawning, handoff parsing, queue advancement, learnings capture.
Progress reporting:
The /ralph invocation reports progress per task. The pipeline relays this:
$ Processing {DOMAIN:note} 1/{total}: {title}
$ create... done
$ reflect... done (3 connections found)
$ reweave... done (2 {DOMAIN:note_plural} updated)
$ verify... done (PASS)
For large batches (20+ claims): /ralph handles context isolation automatically via subagents. The pipeline does NOT need to chunk — /ralph processes N tasks sequentially with fresh context per phase.
Phase 4: Verify Completion
After /ralph finishes, verify all tasks for this batch are done.
Check the queue: count tasks for this batch that are NOT done.
If tasks remain pending:
- Report which tasks are incomplete and at which phase
- Show the specific task IDs and their current_phase
- Suggest: "Run
/ralph --batch {batch_id}to continue from where it stopped" - Do NOT proceed to archive
If all tasks are done: Proceed to Phase 5.
Phase 5: Archive Batch
When all tasks for the batch are complete, archive the batch.
How to invoke:
/archive-batch {batch_id}
Or execute directly:
- Move all task files from
ops/queue/toops/queue/archive/{date}-{batch_id}/ - Generate a batch summary file:
{batch_id}-summary.md - Remove completed entries from the queue (or mark as archived)
The summary should include:
- Source file name and original location
- Number of claims extracted
- Number of enrichments
- List of created {DOMAIN:note_plural} with titles
- Any notable learnings from the batch
Phase 6: Final Report
--=={ pipeline }==--
Source: {source_file}
Batch: {batch_id}
Extraction:
{DOMAIN:note_plural} extracted: {N}
Enrichments identified: {M}
Processing:
{DOMAIN:note_plural} created: {N}
Existing {DOMAIN:note_plural} enriched: {M}
Connections added: {C}
{DOMAIN:topic map}s updated: {T}
Older {DOMAIN:note_plural} updated via reweave: {R}
Quality:
All verify checks: {PASS/FAIL count}
Archive: ops/queue/archive/{date}-{batch_id}/
Summary: {batch_id}-summary.md
{DOMAIN:note_plural} created:
- [[claim title 1]]
- [[claim title 2]]
- ...
If --handoff flag was set, also output:
=== RALPH HANDOFF: pipeline ===
Target: {source_file}
Work Done:
- Seeded source: {batch_id}
- Extracted {N} {DOMAIN:note_plural} and {M} enrichments
- Processed all claims through 4-phase pipeline
- Archived batch to {archive_path}
Files Modified:
- {DOMAIN:notes}/ ({N} new {DOMAIN:note_plural})
- ops/queue/archive/{date}-{batch_id}/ (archived)
Learnings:
- [Friction]: {description} | NONE
- [Surprise]: {description} | NONE
- [Methodology]: {description} | NONE
- [Process gap]: {description} | NONE
Queue Updates:
- All tasks for batch {batch_id} marked done and archived
=== END HANDOFF ===
Error Handling
Phase failure at any stage:
- Report the failure with context (which phase, which task, what error)
- Show the current queue state for this batch
- Suggest remediation: "Run
/ralph --batch {batch_id}to continue from where it stopped" - Do NOT attempt to continue automatically past failures
The pipeline is resumable. Queue state persists across sessions:
- /seed detects prior processing and asks whether to proceed
- /ralph picks up from the last completed phase (queue is the source of truth)
- /archive-batch verifies completeness before archiving
Seed failure: If /seed fails (file not found, duplicate detected and user declines), stop the pipeline entirely.
Extract failure: If /reduce extracts zero claims, report and stop. Do not proceed to an empty processing phase.
Processing failure: If /ralph fails mid-batch, the queue preserves state. Individual claims resume from their failed phase on next /ralph invocation.
Archive failure: If archiving fails, the claims are still created and connected. Only the organizational cleanup is missing — re-run /archive-batch manually.
Resumability
The pipeline is designed to be interrupted and resumed at any point:
| Interrupted At | How to Resume |
|---|---|
| Before seed | Run /pipeline again (starts fresh) |
| After seed, before reduce | /ralph 1 --batch {id} --type extract |
| After reduce, during claims | /ralph --batch {id} (picks up from failed phase) |
| After all claims, before archive | /archive-batch {id} |
State lives in the queue file. The pipeline reads queue state, not session state. This means you can interrupt, close the session, and resume later.
Edge Cases
No target file: List {DOMAIN:inbox}/ candidates, suggest the best one based on age and relevance.
Source already seeded: /seed detects this and asks the user. If they decline, the pipeline stops cleanly.
Large source (2500+ lines): /reduce handles chunking automatically. The pipeline does not need special handling.
No ops/derivation-manifest.md: Use universal vocabulary for all output.
Critical Constraints
never:
- Skip the seed phase (duplicate detection is important)
- Continue past a failed phase automatically
- Process claims inline instead of via /ralph subagents
- Archive a batch with incomplete tasks
always:
- Report progress at each phase boundary
- Verify all tasks are done before archiving
- Show the user what was created (list of {DOMAIN:note_plural})
- Suggest next steps if interrupted
- Use domain-native vocabulary from derivation manifest