PipelineSAFE
Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.
Overview
Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.
9eccf964e924OBSERVED · 2026-10-07What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: pipeline
description: 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".
version: "1.0"
generated_from: "arscontexta-v1.6"
user-invocable: true
context: fork
model: sonnet
allowed-tools: Read, Write, Edit, Grep, Glob, Bash, Task
argument-hint: "[file] — path to source file to process end-to-end"
---
## EXECUTE NOW
**Target: $ARGUMENTS**
Parse immediately:
- Source file path: the file to process (required)
- `--handoff`: output RALPH HANDOFF block at end (for chaining)
- If target is empty: list files in {DOMAIN:inbox}/ and ask which to process
### Step 0: Read Vocabulary
Read `ops/derivation-manifest.md` (or fall back to `ops/derivation.md`) for domain vocabulary mapping. All output must use domain-native terms. If neither file exists, use universal terms.
**START NOW.** Run the full pipeline.
---
## Pipeline Overview
The pipeline chains four phases. Each phase uses skill invocation or /ralph for subagent-based processing. State lives in the queue file — the pipeline is stateless orchestration on top of stateful queue entries.
```
Source file
|
v
Phase 1: /seed — create extract task, move source to archive
|
v
Phase 2: /reduce (via /ralph) — extract claims from source
|
v
Phase 3: /ralph (all claims) — create -> reflect -> reweave -> verify
|
v
Phase 4: /archive-batch — move task files, generate summary
|
v
Complete
```
The pipeline is the convenience wrapper. /ralph is the engine. /seed is the entry point.
---
## Phase 1: Seed
Invoke /seed on the target file to create the extract task, check for duplicates, and move the source to its archive folder.
**How to invoke:**
Use the Skill tool if available, otherwise execute the /seed workflow directly:
- Validate source exists
- Check for prior processing (duplicate detection)
- Create archive folder
- Move source from {DOMAIN:inbox} to archive
- Create extract task file
- Add extract task to queue
**Capture from seed output:**
- **Batch ID**: the source basename (used for --batch filtering in subsequent steps)
- **Archive folder path**: where the source was moved
- **next_claim_start**: the claim numbering start
Report: `$ 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:
1. Move all task files from `ops/queue/` to `ops/queue/archive/{date}-{batch_id}/`
2. Generate a batch summary file: `{batch_id}-summary.md`
3. 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} enrichTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
9eccf964e924full audit observations/trust-audit/skill/agenticnotetaking__pipeline.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-07 | 9eccf964e924 | SAFE | B | 89 | first audit |
Questions
What does the Pipeline skill do?
Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.
Is Pipeline safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Pipeline access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (9eccf964e924), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.