scbe-research-publishing-autopilot

Build and operate multi-hour SCBE research-to-publishing loops for articles and social posts with retrigger logic, evidence gates, and performance monitoring. Use when repeatable growth execution must stay lore/code accurate and avoid invention misrepresentation.

6 stars

Best use case

scbe-research-publishing-autopilot is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Build and operate multi-hour SCBE research-to-publishing loops for articles and social posts with retrigger logic, evidence gates, and performance monitoring. Use when repeatable growth execution must stay lore/code accurate and avoid invention misrepresentation.

Teams using scbe-research-publishing-autopilot should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/scbe-research-publishing-autopilot/SKILL.md --create-dirs "https://raw.githubusercontent.com/issdandavis/SCBE-AETHERMOORE/main/external/codex-skills-live/scbe-research-publishing-autopilot/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/scbe-research-publishing-autopilot/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How scbe-research-publishing-autopilot Compares

Feature / Agentscbe-research-publishing-autopilotStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Build and operate multi-hour SCBE research-to-publishing loops for articles and social posts with retrigger logic, evidence gates, and performance monitoring. Use when repeatable growth execution must stay lore/code accurate and avoid invention misrepresentation.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# SCBE Research Publishing Autopilot

## Overview
Run a deterministic campaign loop: research -> draft -> accuracy gate -> schedule -> monitor -> retrigger.
Use this skill for "set and monitor" growth systems, not blind autoposting.

## Workflow
1. Define the campaign contract.
- Capture goals, revenue path, channels, cadence, and guardrails in a JSON campaign file.
- Use `references/gates.yaml` for required thresholds and safety constraints.

2. Build "context of self" from prior work before research.
- Load high-performing past posts and dataset manifests.
- Produce a reusable context artifact with your proven framing, offers, and vocabulary.
- Run `scripts/context_packer.py` to create `self_context_pack.json`.

3. Build a claim-evidence pack before drafting.
- Gather source paths from repo docs/code and lore notes.
- Require each public claim to map to a source file and anchor phrase.
- Run `scripts/claim_gate.py` before any publishing step.

4. Generate platform-specific drafts.
- Build one canonical message, then adapt per channel via `references/channel_templates.md`.
- Keep language concrete: mention verifiable outcomes, boundaries, and links.
- Avoid hype claims, fake urgency, and unverifiable superlatives.

5. Plan multi-hour execution with retrigger rules.
- Use `scripts/campaign_orchestrator.py` to generate a time-boxed run plan (heartbeats and dispatch windows).
- Include cooldown-based retrigger rules for underperforming posts.

6. Execute with 2.5-party monitoring.
- Treat "2.5-party" as internal governance over third-party channels.
- Log every dispatch, metric sample, and retrigger decision to artifacts.
- Use `scripts/retrigger_monitor.py` to emit next actions from observed metrics.

7. Write daily Obsidian operational notes.
- Use `scripts/write_obsidian_report.py` to convert artifacts into a Context Room report.
- Keep daily traceability for claims, dispatches, and retrigger decisions.

8. Run the multi-hour supervisor for continuous operation.
- Use `scripts/runtime_supervisor.py` for end-to-end looping execution.
- Keep approval gate enabled by default.

## Required Gates
Apply these gates in order before posting:

1. `Evidence Gate`
- Every major claim has `source` and `anchor`.
- Claim source points to local docs/code/lore notes.

2. `Lore and Code Consistency Gate`
- Reject wording that conflicts with canonical terms or implementation reality.
- Prefer exact module/spec names over broad marketing labels.

3. `Policy and Platform Gate`
- Respect platform Terms, disclosure rules, and anti-spam constraints.
- Do not fabricate testimonials, endorsements, or partner claims.

4. `Revenue Integrity Gate`
- Match CTA to an actual offer path (commission, service, SaaS trial, consultation).
- Reject "easy money" language unless tied to concrete constraints and proof.

## Core Commands
Build context-of-self pack:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\context_packer.py `
  --posts-history .\artifacts\past_posts.jsonl `
  --dataset-manifest .\artifacts\datasets_manifest.json `
  --out .\artifacts\self_context_pack.json
```

Validate claim evidence:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\claim_gate.py `
  --posts .\artifacts\campaign_posts.json `
  --repo-root C:\Users\issda\SCBE-AETHERMOORE `
  --out .\artifacts\claim_gate_report.json
```

Create a multi-hour execution plan:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\campaign_orchestrator.py `
  --campaign .\artifacts\campaign.json `
  --out .\artifacts\dispatch_plan.json
```

Evaluate metrics and emit retrigger actions:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\retrigger_monitor.py `
  --metrics .\artifacts\metrics.jsonl `
  --rules .\artifacts\retrigger_rules.json `
  --out .\artifacts\retrigger_actions.json
```

Dispatch to real endpoints with strict approval:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\publish_dispatch.py `
  --plan .\artifacts\dispatch_plan.json `
  --posts .\artifacts\campaign_posts.json `
  --connectors .\artifacts\connectors.json `
  --approval .\artifacts\approvals.json `
  --claim-report .\artifacts\claim_gate_report.json `
  --out-log .\artifacts\dispatch_log.jsonl `
  --state .\artifacts\dispatch_state.json
```

Write daily Obsidian report:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\write_obsidian_report.py `
  --vault-dir "C:\Users\issda\OneDrive\Documents\DOCCUMENTS\A follder" `
  --dispatch-log .\artifacts\dispatch_log.jsonl `
  --claim-report .\artifacts\claim_gate_report.json `
  --retrigger-actions .\artifacts\retrigger_actions.json `
  --self-context .\artifacts\self_context_pack.json `
  --campaign-id scbe-autopilot
```

Run end-to-end supervisor:
```powershell
python C:\Users\issda\.codex\skills\scbe-research-publishing-autopilot\scripts\runtime_supervisor.py `
  --working-dir .\artifacts\runtime `
  --repo-root C:\Users\issda\SCBE-AETHERMOORE `
  --campaign .\artifacts\campaign.json `
  --posts .\artifacts\campaign_posts.json `
  --posts-history .\artifacts\past_posts.jsonl `
  --dataset-manifest .\artifacts\datasets_manifest.json `
  --connectors .\artifacts\connectors.json `
  --approval .\artifacts\approvals.json `
  --retrigger-rules .\artifacts\retrigger_rules.json `
  --metrics .\artifacts\metrics.jsonl `
  --vault-dir "C:\Users\issda\OneDrive\Documents\DOCCUMENTS\A follder" `
  --campaign-id scbe-autopilot
```

## Output Artifacts
Write these files per run:
- `campaign.json`: objective, channels, runtime, cadence.
- `self_context_pack.json`: ranked prior-post signals + dataset context.
- `campaign_posts.json`: channel-ready post payloads with claim mappings.
- `claim_gate_report.json`: pass/fail per claim with missing source list.
- `dispatch_plan.json`: timed actions for the run window.
- `dispatch_log.jsonl`: endpoint dispatch results and gate outcomes.
- `dispatch_state.json`: idempotency state to prevent duplicate sends.
- `metrics.jsonl`: observed post metrics snapshots.
- `retrigger_actions.json`: follow-up actions after rule evaluation.
- `retrigger_state.json`: cooldown memory for retrigger decisions.
- `Context Room/Reports/*.md`: daily operational notes for auditability.

## Operational Defaults
- Use 4-12 hour runtime windows.
- Use 15-minute heartbeat intervals.
- Use 60-minute retrigger cooldown unless campaign rules override.
- Keep one canonical long-form source per topic before short-form variants.
- Require human review when confidence is low or claims are novel.

## References
- Read `references/runbook.md` for execution order and handoff protocol.
- Read `references/channel_templates.md` for channel structure and tone.
- Read `references/gates.yaml` for thresholds and disallowed behaviors.
- Read `references/connectors.md` for endpoint/approval schemas.

Related Skills

scbe-training-pair-authoring

6
from issdandavis/SCBE-AETHERMOORE

Create prompt and response and metadata training pairs from SCBE documents, repair traces, terminal sessions, and operational workflows using the repository's canonical dataset contract and provenance rules.

scbe-spin-conversation-engine

6
from issdandavis/SCBE-AETHERMOORE

Generate SFT training data via radial matrix conversation pivots with D&D-style combat research mode. Produces diverse, cost-effective training pairs with Sacred Tongue encoding, golden spiral problem distribution, and harmonic re-attunement.

scbe-research-training-bridge

6
from issdandavis/SCBE-AETHERMOORE

Stage arXiv evidence and Obsidian markdown into source-grounded Hugging Face training bundles for research, review, and later SFT runs.

scbe-document-management

6
from issdandavis/SCBE-AETHERMOORE

Consolidate overlapping docs, classify files by authority, and keep SCBE repo documents aligned with runtime truth. Use when the repo has drift between canonical docs, public docs, proposal notes, research branches, and generated evidence.

scbe-colab-bridge

6
from issdandavis/SCBE-AETHERMOORE

Control Google Colab notebooks from Claude Code via Chrome extension. Execute cells, run terminal commands, read outputs, and manage GPU compute remotely.

scbe-claim-to-code-evidence

6
from issdandavis/SCBE-AETHERMOORE

Map SCBE Notion technical claims, proof pages, and patent-facing architecture notes to concrete repository evidence such as code paths, tests, demos, and docs. Use when Codex needs to build a due-diligence packet, claim-to-code audit, implementation crosswalk, patent support note, or proof summary from local Notion exports and repo artifacts.

scbe-autonomous-worker-productizer

6
from issdandavis/SCBE-AETHERMOORE

Turn SCBE automation, autonomous worker, and revenue-system notes into concrete offers, workflow packs, pilot plans, or SaaS-facing product packets. Use when Codex needs to package Notion automation pages into buyer-ready offerings, n8n/Zapier workflow designs, flock-backed worker systems, or implementation roadmaps tied to existing SCBE repo surfaces.

scbe-code-scanning-ops

6
from issdandavis/SCBE-AETHERMOORE

Operate GitHub code scanning and CodeQL remediation for SCBE repositories. Use when triaging code-scanning alerts, mapping alert classes to fix patterns, validating targeted regressions, or wiring dedicated CodeQL workflows and runbooks into the repo.

scbe-world-anvil-lore-rag-7th-tongue

6
from issdandavis/SCBE-AETHERMOORE

Build and operate a lore-focused RAG system using World Anvil exports and SCBE docs, with deterministic Claude/Codex cross-talk packets for handoff. Use when users ask to structure lore canon retrieval, sync worldbuilding data, enforce citation-grounded generation, or coordinate a 7th Tongue overseer lane across multiple AI agents.

scbe-webtoon-book-conversion

6
from issdandavis/SCBE-AETHERMOORE

Convert The Six Tongues Protocol and related manuscript sections into webtoon/manhwa storyboard packets, episode roadmaps, panel expansion plans, and image-generation-ready prompt lanes. Use when extending the series storyboard, adapting book chapters into vertical scroll episodes, or keeping art generation tied to canon instead of drifting into generic fantasy panels.

scbe-voice-render-verification

6
from issdandavis/SCBE-AETHERMOORE

Govern and verify SCBE voice rendering work that maps Langues weighting into breath, phase, and Layer 14 audio-axis packets. Use when implementing or reviewing `scripts/voice_gen_hf.py`, emitting sidecar voice packets, validating canonical tongue ordering, tuning breath planning or phase timing, or keeping voice docs and code aligned with `docs/LANGUES_WEIGHTING_SYSTEM.md` and `docs/specs/SCBE_VOICE_EMOTIONAL_TIMBRE_SYSTEM.md`.

scbe-universal-synthesis

6
from issdandavis/SCBE-AETHERMOORE

Orchestrate all installed Codex skills through an auto-updating synthesis matrix with Sacred Tongues routing, emotion/intent metadata, and decodable lexicon packets tied to established SCBE characters. Use when the user asks for cross-skill coordination, auto skill updates, multi-skill routing, or Sacred Tongues intent mapping.