Reddit Moderate

Reddit Moderate

On-demand Reddit community moderation powered by PRAW. Fetches your modqueue, classifies content against subreddit rules and author history using LLM-powered report classification, and executes mod actions you confirm.

Modes

| Mode | Invocation | Behavior | |------|-----------|----------| | Interactive | /reddit-moderate | Fetch queue, classify, present with analysis, you confirm actions | | Auto | /loop 10m /reddit-moderate --auto | Fetch queue, classify, auto-action high-confidence items, flag rest | | Dry-run | /reddit-moderate --dry-run | Fetch queue, classify, show recommendations without acting |

Reference Loading Table

| Signal | Load These Files | Why | |---|---|---| | Classifying items, category definitions, confidence thresholds | classification-prompt.md | Routes to the matching deep reference | | Prompt template, untrusted content handling, prompt injection defense | classification-prompt.md | Routes to the matching deep reference | | Action mapping by confidence level, config.json format | classification-prompt.md | Routes to the matching deep reference | | Per-item classification steps, repeat offender check, mass-report detection | classification-prompt.md | Routes to the matching deep reference | | Script subcommands, flags, usage examples | script-commands.md | Routes to the matching deep reference | | Exit codes, error troubleshooting | script-commands.md | Routes to the matching deep reference | | Scan commands, setup commands, queue/report commands | script-commands.md | Routes to the matching deep reference | | Subreddit data directory structure, file purposes | context-loading.md | Routes to the matching deep reference | | Setup flow for new subreddits, bootstrapping | context-loading.md | Routes to the matching deep reference | | Credentials, prerequisites, dry-run default | context-loading.md | Routes to the matching deep reference | | Context loading sequence, missing file handling | context-loading.md | Routes to the matching deep reference |

Instructions

Interactive Mode (default)

Phase 1: FETCH -- Get the modqueue with classification prompts.

python3 skills/content/reddit-moderate/scripts/reddit-mod.py queue --json --limit 25 | python3 skills/content/reddit-moderate/scripts/reddit-mod.py classify

This pipes modqueue items through the classify subcommand, which loads subreddit context from reddit-data/{subreddit}/ and assembles a classification prompt for each item. The output is a JSON array where each result contains item metadata, heuristic flags (mass_report_flag, repeat_offender_count), and a prompt field with the fully rendered classification prompt.

The classify subcommand is a prompt assembler only; it does not call any LLM. Fields classification, confidence, and reasoning are null/empty placeholders for the LLM to fill in Phase 2.

Read the output. For each item, read the prompt field and classify it.

Phase 2: CLASSIFY -- For each item, read the rendered classification prompt and assign a classification. The prompt contains all subreddit context, rules, author history, and report signals. Classify as one of: FALSE_REPORT, VALID_REPORT, MASS_REPORT_ABUSE, SPAM, BAN_RECOMMENDED, NEEDS_HUMAN_REVIEW.

Assign a confidence score (0-100) and one-sentence reasoning for each item.

> Load references/classification-prompt.md for category definitions, the full > prompt template, per-item classification steps, and confidence thresholds.

Phase 3: PRESENT -- For each modqueue item, present a summary grouped by classification. Include the classification label and confidence:

Item 1: [t3_abc123] "Post title here"
  Author: u/username (score: 5, reports: 2)
  Report reasons: "spam", "off-topic"
  Body: [first 200 chars of content]
  Classification: VALID_REPORT (confidence: 92%)
  Reasoning: Author history shows 5 promotional posts in 7 days with no
             community engagement. Violates subreddit rules against self-promotion.
  Recommendation: REMOVE (reason: Rule 3)

Item 2: [t1_def456] "Comment text here"
  Author: u/other_user (score: 12, reports: 1)
  Report reason: "rude"
  Classification: FALSE_REPORT (confidence: 88%)
  Reasoning: Sarcastic but within community norms. Report appears frivolous.
  Recommendation: APPROVE

Phase 4: CONFIRM -- Ask the user to confirm or override recommendations. Wait for user input. Wait for explicit user confirmation before proceeding.

Phase 5: ACT -- Execute confirmed actions:

python3 skills/content/reddit-moderate/scripts/reddit-mod.py approve --id t1_def456
python3 skills/content/reddit-moderate/scripts/reddit-mod.py remove --id t3_abc123 --reason "Rule 3: Self-promotion"

Report results after each action.

> Load references/script-commands.md for all subcommand flags and examples.

Auto Mode (for /loop)

When invoked with --auto argument or when the user says "auto mode":

1. Fetch queue and build classification prompts:

``bash python3 skills/content/reddit-moderate/scripts/reddit-mod.py queue --auto --since-minutes 15 --json | python3 skills/content/reddit-moderate/scripts/reddit-mod.py classify ``

1. For each item, read the rendered prompt field and classify it using

the categories and confidence scoring from references/classification-prompt.md.

1. For items meeting the confidence threshold:

• FALSE_REPORT / MASS_REPORT_ABUSE => approve
• SPAM => remove as spam
• VALID_REPORT => remove with generated reason
• BAN_RECOMMENDED => always skip (requires human review regardless of confidence)

1. For items below the confidence threshold => skip (leave for human review).

1. Output a summary of actions taken, items skipped, and classifications.

Critical auto-mode rules:

• Always require human review before banning users
• Always require human review before locking threads
• When in doubt, SKIP; false negatives are better than false positives
• Log every auto-action for the user to review later

Proactive Scan Mode

Scan recent posts/comments for rule violations that were not reported:

python3 skills/content/reddit-moderate/scripts/reddit-mod.py scan --json --classify --limit 50 --since-hours 24

With --classify, the scan output includes classification prompts. Read each prompt and classify the item. Items with scan_flags (jobadpattern, trainingvendorpattern, possiblenonenglish) have heuristic signals that supplement the LLM classification.

Same confidence thresholds and safety rules as auto mode apply.

Reference Loading

Load these references when the task matches the signal:

| Signal / Task | Reference File | |---------------|----------------| | Classifying items, category definitions, confidence thresholds | references/classification-prompt.md | | Prompt template, untrusted content handling, prompt injection defense | references/classification-prompt.md | | Action mapping by confidence level, config.json format | references/classification-prompt.md | | Per-item classification steps, repeat offender check, mass-report detection | references/classification-prompt.md | | Script subcommands, flags, usage examples | references/script-commands.md | | Exit codes, error troubleshooting | references/script-commands.md | | Scan commands, setup commands, queue/report commands | references/script-commands.md | | Subreddit data directory structure, file purposes | references/context-loading.md | | Setup flow for new subreddits, bootstrapping | references/context-loading.md | | Credentials, prerequisites, dry-run default | references/context-loading.md | | Context loading sequence, missing file handling | references/context-loading.md |

References

This skill uses these shared patterns:

• [Untrusted Content Handling](../shared-patterns/untrusted-content-handling.md) - Prompt injection defense for all Reddit content fed into LLM classification

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: notque
• Source: notque/vexjoy-agent
• License: MIT
• Homepage: https://vexjoy.com

Install and usage instructions live in the source repository linked above.