Prompt & Automation Catalogue¶
What it is¶
The Prompt & Automation Catalogue is the central repository for every LLM prompt, GitHub Action workflow, and autonomous script used to keep this repository growing. As of June 2026, it includes specialized system prompts for multi-agent KnowledgeOps and automated quality audits.
What problem it solves¶
Autonomous systems can often feel like "black boxes." This catalogue solves the problem of opacity by documenting the exact logic, schedules, and instructions used by agents like Jules. It allows for easier debugging, auditing of AI-generated content, and systematic tuning of prompt performance over time.
Where it fits in the stack¶
Category: Architecture / Governance. It sits in the metacognition and orchestration layer, documenting the workflows that manage all other content in the repository.
Typical use cases¶
- Prompt Versioning: Tracking changes to the system prompts used by the Daily Jules Maintenance workflow.
- Workflow Auditing: Reviewing the schedule and logic of recurring GitHub Actions like the Daily AI Digest.
- Agent Onboarding: Providing a clear set of instructions and "mission statements" for new autonomous workers added to the repo.
- Troubleshooting: Identifying why a particular automated task failed by examining its input prompts and execution rules.
Strengths¶
- Transparency: Makes the repository's automated processes understandable to human contributors.
- Reproducibility: Provides the exact prompts needed to replicate the automated workflows in other environments.
- Centralization: Collects disparate GitHub Actions and local scripts into a single, searchable document.
- Standardization: Enforces the use of "High Confidence" documentation standards across all automated outputs.
Limitations¶
- Maintenance Overhead: Requires manual updates whenever a workflow or prompt is changed in the underlying code.
- Complexity: As the number of agents and workflows grows, the catalogue can become difficult to navigate.
- Sensitivity: Some prompts may contain logic that is specific to the current repository structure.
When to use it¶
- When you need to understand how the repository is being maintained automatically.
- When you are designing a new automated workflow and want to ensure it follows existing patterns.
- During quality audits to verify that agents are operating within their defined "Allowed scope."
When not to use it¶
- For documenting tool-specific features that are already covered in their respective canonical pages.
- For storing API keys or other secrets.
Getting started¶
To use the catalogue, identify the automation type (Recurring GA, One-Shot Jules, or Recurring Jules) and locate its mission statement and prompt logic below.
Overview¶
| ID | Name | Runner | Cadence | Type |
|---|---|---|---|---|
| GA-1 | Daily AI Digest | GitHub Actions | 2×/day | Recurring |
| GA-2 | Digest → Intake Bridge | GitHub Actions + OpenRouter LLM | 2×/day | Recurring |
| GA-3 | Daily Jules Maintenance | GitHub Actions → Jules | 2×/day | Recurring |
| GA-4 | Weekly Growth Planner | GitHub Actions → Jules | 2×/week | Recurring |
| J-1 | Fill Infrastructure Category | Jules scheduled task | Once (Day 1) | One-shot |
| J-2 | Fill Frameworks Category | Jules scheduled task | Once (Day 1) | One-shot |
| J-3 | Fill Providers Category | Jules scheduled task | Once (Day 1) | One-shot |
| J-4 | Fill Agents Category | Jules scheduled task | Once (Day 1) | One-shot |
| J-5 | Add Code Examples (Batch 1) | Jules scheduled task | Once (Day 1) | One-shot |
| J-6 | Add Code Examples (Batch 2) | Jules scheduled task | Once (Day 1) | One-shot |
| J-7 | Essential Reading List | Jules scheduled task | Once (Day 1) | One-shot |
| J-8 | RAG Pattern Deep Dive | Jules scheduled task | Once (Day 1) | One-shot |
| J-9 | MCP & Tool-Calling Pattern | Jules scheduled task | Once (Day 1) | One-shot |
| J-10 | Landscape Overview | Jules scheduled task | Once (Day 1) | One-shot |
| JR-1 | Daily Intake Processing | Jules scheduled task | Daily | Recurring |
| JR-2 | Weekly Doc Deepening | Jules scheduled task | Weekly (Mon) | Recurring |
| JR-3 | Weekly Cross-Linking | Jules scheduled task | Weekly (Mon) | Recurring |
| JR-4 | Monthly Landscape Refresh | Jules scheduled task | Monthly (1st) | Recurring |
| JR-5 | Monthly Quality Audit | Jules scheduled task | Monthly (1st) | Recurring |
GitHub Actions — Recurring Workflows¶
GA-1: Daily AI Digest¶
| Workflow | .github/workflows/daily-digest.yml |
| Schedule | 0 0 * * * and 0 12 * * * (00:00 & 12:00 UTC) |
| Secrets | OPENROUTER_API_KEY |
| What it does | Fetches RSS feeds from ai-daily-digest/sources.yaml, summarises new items via OpenRouter, and writes a digest to ai-daily-digest/daily/YYYY-MM-DD.md. Commits and pushes to main. |
GA-2: Digest-Intake Bridge¶
| Workflow | .github/workflows/digest-to-intake.yml |
| Schedule | 0 1 * * * and 0 13 * * * (01:00 & 13:00 UTC) |
| Script | scripts/digest_to_intake.py |
| Secrets | OPENROUTER_API_KEY |
| Models | Llama 3.3 70B → DeepSeek R1 → Qwen 2 7B (fallback chain) |
LLM System Prompt¶
You are an AI tools curator. Given a list of items from a daily AI digest,
identify ONLY items that are specific, named tools, libraries, frameworks,
platforms, or providers in the AI/LLM/ML space. Exclude: general news
articles, opinion pieces, discussions, job posts, hardware announcements
without a software tool, and generic blog posts.
For each qualifying item, output a JSON array of objects:
{"title": "Tool Name", "url": "https://...", "tags": "tool, framework",
"notes": "One-line description"}
Tags must be from: tool, framework, provider, paper/article,
benchmark/eval, infrastructure, analysis
If nothing qualifies, return an empty array: []
Return ONLY valid JSON. No markdown wrapping.
GA-3: Daily Jules Maintenance¶
| Workflow | .github/workflows/daily-jules-maintenance.yml |
| Schedule | 0 7 * * * and 0 19 * * * (07:00 & 19:00 UTC) |
| Issue template | .github/issue-templates/daily-jules-maintenance.md |
Full Issue Prompt (June 2026 Version)¶
## Daily Maintenance Run - @jules
This is an automated daily maintenance task. Please complete the steps
below **in order**, stopping at the first step that produces meaningful
work. Do not attempt all three steps in a single PR.
---
### Step 1 - Process the intake queue
Use the daily inbox format:
- index file: `docs/new-sources.md`
- daily logs: `docs/new-sources/YYYY-MM-DD.md`
- index links format: `/new-sources/YYYY-MM-DD/`
Find all rows with `Status` = `new` across daily logs.
For each row:
1. Check `data/all_tools.json`, `docs/tools/`, and `docs/services/` for existing page.
2. Classify the entry using the tags in `docs/standards.md`.
3. Create the page using templates.
4. Add to `data/all_tools.json` and `mkdocs.yml` nav.
5. Mark the row as `integrated`.
---
### Step 2 - Doc quality audit (only if Step 1 found nothing to do)
Find up to **3 tool docs** in `docs/tools/` that are missing one or
more sections.
---
### Step 3 - Broken internal links (only if Steps 1 and 2 found nothing)
Scan all Markdown files in `docs/` for internal links. Fix or remove broken ones.
GA-4: Weekly Growth Planner¶
| Workflow | .github/workflows/weekly-planner.yml |
| Schedule | 0 2 * * 1 and 0 2 * * 4 (Monday & Thursday 02:00 UTC) |
| Script | scripts/weekly_planner.py |
Jules Scheduled Tasks — One-Shot (Day 1 Seed)¶
J-1 to J-10: Seeding Prompts¶
These prompts (J-1 to J-10) are used to rapidly seed the knowledge base with infrastructure, frameworks, providers, agents, and code examples. Each prompt defines a specific set of tools and target directories.
Jules Scheduled Tasks — Recurring¶
JR-1: Daily Intake Processing¶
Open the most recent file in docs/new-sources/ and process all rows
with Status: new. Create tool docs, update catalog, and mkdocs.yml.
JR-2: Weekly Doc Deepening¶
Read data/growth-metrics.json and find the shallow_docs list. Add
Getting started, CLI, and API examples to the 5 shortest docs.
JR-3: Weekly Cross-Linking¶
Scan all tool docs in docs/tools/ and add 3-5 related tools to the
## Related tools / concepts section.
JR-4: Monthly Landscape Refresh¶
Update docs/knowledge_base/landscape-overview.md with current tool
counts, most-connected tools, and new additions.
JR-5: Monthly Quality Audit¶
Run CI checks and scan for empty sections or broken links.
CLI examples¶
Automations can be triggered or inspected using the GitHub CLI (gh).
# Trigger the Daily AI Digest workflow manually
gh workflow run daily-digest.yml
# List recent runs of the Daily Jules Maintenance workflow
gh run list --workflow daily-jules-maintenance.yml
# View the log for a specific workflow run
gh run view <run-id> --log
API examples¶
Workflows can be triggered programmatically via the GitHub API.
import requests
# Example: Triggering a repository dispatch event to start an automation
def trigger_workflow(token, owner, repo, event_type):
url = f"https://api.github.com/repos/{owner}/{repo}/dispatches"
headers = {
"Authorization": f"Bearer {token}",
"Accept": "application/vnd.github+json"
}
data = {"event_type": event_type}
response = requests.post(url, headers=headers, json=data)
return response.status_code
# trigger_workflow("YOUR_TOKEN", "joanmarcriera", "Home-office-automations", "daily-audit")
Related tools / concepts¶
- Jules
- Multi-Agent KnowledgeOps
- Automated Contributions
- GitHub Actions
- OpenRouter
- Standards & Conventions
- RAG Pattern
- MCP
Sources / References¶
- GitHub Actions Documentation
- Model Context Protocol Specification
- Automated Contributions (Jules setup)
- Multi-Agent KnowledgeOps Governance
Contribution Metadata¶
- Last reviewed: 2026-06-26
- Confidence: high