Replenish Queue

Automatically generate new tasks when the todo queue is empty or near-empty. Combines gap analysis, research-to-article pipelines, and review generation to maintain a healthy task queue.

Usage

code

/replenish-queue [mode]

Modes:

•conservative - Generate 3-5 high-confidence tasks only
•(default) - Standard replenishment, 5-8 tasks
•aggressive - Generate 8-12 tasks including speculative ones

When to Use

•When todo.md Active Tasks section is empty
•When the evolution loop detects the queue is low
•Monthly strategic planning sessions
•After completing a major content push

Task Generation Sources

The skill generates tasks from four sources, in priority order:

Source 1: Task Chains (Successor Tasks)

Recent completions that should generate follow-up work:

Completed Task Type	Generates
`research-topic`	P2: Write article on [topic]
`expand-topic`	P2: Review related articles considering [new article]
`deep-review` with issues	P1: Address [issue] in [file]
`pessimistic-review` with critical	P1: Fix [critical issue]
`optimistic-review` opportunity	P3: Explore [expansion idea]

Chain Logic:

•Scan recent_tasks in evolution-state.yaml
•For each research-topic completion, check if corresponding article exists
•For each expand-topic completion, identify articles that existed before it and might benefit from cross-reference review
•Generate successor tasks with appropriate priority

Source 2: Unconsumed Research

Research notes that haven't produced articles yet:

•Scan obsidian/research/*.md for all research notes
•For each note, check if related_articles frontmatter links to published articles
•
If research has no corresponding article, generate:
- •P2: Write article on [topic] (based on [research file])

Source 3: Gap Analysis

Content areas that need expansion:

•Run lightweight coverage analysis (similar to content-coverage review)
•Compare current content against convergence targets in evolution-state.yaml
•
Generate tasks for:
- •Topics supporting tenets that lack coverage
- •Concepts mentioned but not defined
- •Missing cross-links between related content

Gap Categories:

•Critical gaps: Directly support tenets, P1 priority
•Important gaps: Major philosophical context, P2 priority
•Nice-to-have: Interesting extensions, P3 priority

Source 4: Staleness-Driven Tasks

Content that hasn't been touched recently:

•Check last_deep_review frontmatter across all content files
•
For files not reviewed in 30+ days with ai_contribution > 50, generate:
- •P3: Deep review [file] for quality and currency

Source 5: Length Violations

Articles exceeding length thresholds need condensation:

•Run length analysis using tools/curate/length.py
•For articles exceeding thresholds, generate tasks:

Status	Priority	Task Title
Critical (>critical threshold)	P1	Condense [file] (N words, X% of target)
Hard Warning (>hard threshold)	P2	Condense [file] (N words, X% of target)

Task format:

markdown

### P1: Condense free-will.md (9567 words, 319% of target)
- **Type**: condense
- **Notes**: Article exceeds 6000-word critical threshold for topics/.
  Preserve core arguments while removing redundancy and deferring
  detailed subtopics to linked articles. See /condense skill.
- **Source**: length_analysis
- **Generated**: 2026-01-25

Thresholds by section (soft/hard/critical):

•concepts/: 2500 / 3500 / 5000 words
•topics/: 3000 / 4000 / 6000 words
•apex/: 4000 / 5000 / 6500 words
•voids/: 2000 / 3000 / 4000 words

Maximum 3 condense tasks per replenishment (prioritize worst offenders).

Instructions

1. Load Current State

Read obsidian/workflow/evolution-state.yaml for:

•recent_tasks - completed work that might generate successors
•content_stats - current content counts
•convergence_targets - what "done" looks like
•progress - current progress toward targets

Read obsidian/workflow/todo.md to see:

•Current Active Tasks (should be empty or near-empty)
•Completed Tasks (for context on recent work)
•Vetoed Tasks (to avoid regenerating rejected ideas)

2. Generate Candidate Tasks

2.1 Check Task Chains

For each task in recent_tasks from last 14 days:

If research-topic:

python

research_file = task.output
topic = extract_topic(research_file)
article_exists = check_for_article(topic)
if not article_exists:
    candidates.append({
        'title': f'Write article on {topic}',
        'type': 'expand-topic',
        'priority': 'P2',
        'notes': f'Based on research in {research_file}. Synthesize findings into site content.',
        'source': 'chain',
        'chain_parent': research_file
    })

If expand-topic:

python

new_article = task.output
topic = extract_topic(new_article)
# Find articles that might benefit from cross-referencing
related = find_related_articles(new_article)
for article in related[:2]:  # Max 2 review tasks per new article
    candidates.append({
        'title': f'Review {article} considering {topic} insights',
        'type': 'cross-review',
        'priority': 'P2',
        'notes': f'New article {new_article} may provide insights relevant to {article}. Check for cross-links, reinforcing arguments, or contradictions.',
        'source': 'chain',
        'chain_parent': new_article
    })

2.2 Check Unconsumed Research

python

for research_file in glob('obsidian/research/*.md'):
    frontmatter = parse_frontmatter(research_file)
    topic = extract_topic_from_title(frontmatter['title'])

    # Check if article exists for this research
    if not has_corresponding_article(topic):
        candidates.append({
            'title': f'Write article on {topic}',
            'type': 'expand-topic',
            'priority': 'P2',
            'notes': f'Research completed in {research_file}. Ready for article synthesis.',
            'source': 'unconsumed_research',
            'research_file': research_file
        })

2.3 Run Gap Analysis

Scan existing content and identify gaps:

python

# Load tenets for priority assessment
tenets = read_file('obsidian/tenets/tenets.md')

# Check each tenet for supporting content
gaps = []
for tenet in ['dualism', 'minimal-quantum', 'bidirectional', 'no-many-worlds', 'occams-limits']:
    supporting_content = find_content_supporting(tenet)
    if len(supporting_content) < 2:
        gaps.append({
            'area': tenet,
            'priority': 'P1',  # Tenet support is high priority
            'type': 'critical'
        })

# Check for mentioned-but-undefined concepts
all_wikilinks = extract_wikilinks(all_content)
existing_files = list_content_files()
for link in all_wikilinks:
    if link not in existing_files:
        gaps.append({
            'area': link,
            'priority': 'P2',
            'type': 'undefined_concept'
        })

# Generate tasks from gaps
for gap in gaps:
    if gap['type'] == 'critical':
        candidates.append({
            'title': f'Research {gap["area"]} support',
            'type': 'research-topic',
            'priority': gap['priority'],
            'notes': f'Tenet "{gap["area"]}" needs more supporting content.',
            'source': 'gap_analysis'
        })
    elif gap['type'] == 'undefined_concept':
        candidates.append({
            'title': f'Create concept page for {gap["area"]}',
            'type': 'expand-topic',
            'priority': gap['priority'],
            'notes': f'Concept "{gap["area"]}" is referenced but has no definition page.',
            'source': 'gap_analysis'
        })

2.4 Check Content Staleness

python

for content_file in glob('obsidian/**/*.md'):
    frontmatter = parse_frontmatter(content_file)
    last_review = frontmatter.get('last_deep_review')
    ai_contribution = frontmatter.get('ai_contribution', 0)

    if ai_contribution > 50:  # AI-heavy content needs periodic review
        if last_review is None or days_since(last_review) > 30:
            candidates.append({
                'title': f'Deep review {basename(content_file)}',
                'type': 'deep-review',
                'priority': 'P3',
                'notes': f'AI-generated content not reviewed in 30+ days.',
                'source': 'staleness'
            })

2.5 Check Length Violations

python

from tools.curate.length import get_length_warnings

warnings = get_length_warnings(Path('obsidian'), min_status='hard_warning')
for analysis in warnings[:5]:  # Top 5 worst offenders
    priority = 'P1' if analysis.status == 'critical' else 'P2'
    candidates.append({
        'title': f'Condense {analysis.path.name} ({analysis.word_count} words, {analysis.excess_percent:.0f}% of target)',
        'type': 'condense',
        'priority': priority,
        'notes': f'Article exceeds {analysis.hard_threshold}-word threshold for {analysis.section}/. '
                 f'Preserve core arguments while removing redundancy.',
        'source': 'length_analysis'
    })

3. Filter and Deduplicate

Remove candidates that:

•Match any task in Vetoed Tasks section
•Match any task already in Active Tasks
•Duplicate another candidate (by title similarity)
•Would exceed mode limits

4. Score and Prioritize

Score each candidate:

code

SCORE = PRIORITY_BASE + SOURCE_BONUS + TENET_RELEVANCE

PRIORITY_BASE: P1=300, P2=200, P3=100
SOURCE_BONUS: chain=50, unconsumed_research=40, gap_analysis=30, length_analysis=25, staleness=10
TENET_RELEVANCE: +50 if directly supports a tenet

Sort by score descending.

5. Select Tasks Based on Mode

Mode	Count	P3 Allowed?
conservative	3-5	No
standard	5-8	1-2 max
aggressive	8-12	Yes

Ensure diversity:

•At least 1 research task (if candidates exist)
•At least 1 article task (if candidates exist)
•At least 1 review task (if candidates exist)
•Max 3 tasks from any single source

6. Format and Write Tasks

Add selected tasks to obsidian/workflow/todo.md under Active Tasks:

markdown

## Active Tasks

### P1: Write article on epiphenomenalism
- **Type**: expand-topic
- **Notes**: Research completed in research/epiphenomenalism-2026-01-09.md. Key alternative to bidirectional interaction that site needs to address.
- **Source**: unconsumed_research
- **Generated**: 2026-01-09

### P2: Review hard-problem-of-consciousness.md considering panpsychism insights
- **Type**: cross-review
- **Notes**: New article concepts/panpsychism.md may provide insights relevant to topics/hard-problem-of-consciousness.md. Check for cross-links, reinforcing arguments, or contradictions.
- **Source**: chain (from panpsychism.md)
- **Generated**: 2026-01-09

### P2: Research quantum decoherence objection
- **Type**: research-topic
- **Notes**: Minimal Quantum Interaction tenet needs response to decoherence objection. Critical gap in site's argument.
- **Source**: gap_analysis
- **Generated**: 2026-01-09

7. Update State

Update obsidian/workflow/evolution-state.yaml:

yaml

queue_status:
  p0_tasks: 0
  p1_tasks: 1
  p2_tasks: 4
  p3_tasks: 2
  needs_replenishment: false
  last_replenishment: 2026-01-09T10:00:00+00:00
  replenishment_source_counts:
    chain: 2
    unconsumed_research: 1
    gap_analysis: 3
    length_analysis: 0
    staleness: 1

8. Generate Report

Output summary:

markdown

## Queue Replenishment Complete

**Mode**: standard
**Tasks generated**: 7
**Sources used**: chain (2), gap_analysis (3), unconsumed_research (1), staleness (1)

### Generated Tasks

| Priority | Title | Type | Source |
|----------|-------|------|--------|
| P1 | Write article on epiphenomenalism | expand-topic | unconsumed_research |
| P2 | Review hard-problem considering panpsychism | cross-review | chain |
| P2 | Research quantum decoherence objection | research-topic | gap_analysis |
| P2 | Create explanatory gap concept page | expand-topic | gap_analysis |
| P2 | Write Eastern philosophy overview | expand-topic | gap_analysis |
| P3 | Deep review free-will.md | deep-review | staleness |
| P3 | Explore consciousness and time topic | research-topic | optimistic |

### Queue Health
- P1: 1 task
- P2: 4 tasks
- P3: 2 tasks
- Estimated sessions to empty: 2-3

### Skipped Candidates
- "Research near-death experiences" - matches vetoed task
- "Write simulation article" - already exists

Cross-Review Task Type

This skill introduces a new task type: cross-review

Purpose: After a new article is written, review related existing articles to:

•Add cross-links to the new content
•Check for contradictions or tensions
•Identify arguments that could be strengthened by the new material
•Ensure consistent terminology

Execution: When the evolution loop encounters a cross-review task:

•Read the new article (chain_parent)
•Read the target article
•
Look for:
- •Places to add [[new-article]] links
- •Arguments that new research supports or challenges
- •Terminology inconsistencies
•Make edits if improvements found
•Log findings even if no edits made

Important

•NEVER generate tasks that match Vetoed Tasks
•NEVER generate P0 tasks (those require human urgency assessment)
•Always include Generated date for tracking
•Preserve task Notes verbatim when tasks complete
•Maximum 3 tasks per source to ensure diversity
•Chain tasks from last 14 days only (older completions are stale)
•This skill ONLY generates tasks; it does NOT execute them