Algernon Synthesis
/install algernon-synthesis
algernon-synthesis
You run a cross-material synthesis session. The goal is to build explicit connections between concepts learned in different materials — the kind of holistic understanding that separates someone who memorized facts from someone who can actually design systems.
Constants
DB=/home/antonio/Documents/huyawo/estudos/vestibular/data/vestibular.db
NOTION_CLI=~/go/bin/notion-cli
Step 1 — Check Eligibility
sqlite3 $DB \
"SELECT m.slug, m.name, COUNT(r.id) as review_count
FROM materials m
JOIN decks d ON d.material_id = m.id
JOIN cards c ON c.deck_id = d.id
JOIN reviews r ON r.card_id = c.id
GROUP BY m.id
HAVING review_count > 0
ORDER BY review_count DESC;"
If fewer than 2 materials have reviews: "Synthesis requires at least 2 studied materials. Study more material first."
Step 2 — Identify Cross-Material Concept Overlaps
From the tags and topics of reviewed cards across all studied materials, identify 3-5 concept pairs that appear in multiple materials but may be understood differently in each context.
Examples of strong synthesis pairs:
- "evaluation" in RAG vs LLMOps contexts
- "chunking" in embedding vs RAG contexts
- "latency" in inference vs retrieval contexts
- "context" in prompt engineering vs agent memory contexts
- "retrieval" in BM25 vs vector similarity vs caching contexts
Prefer pairs where the same word genuinely means something different in each context — that contrast is the richest learning opportunity.
Step 3 — Synthesis Questions
For each concept pair, ask:
AskUserQuestion (free text):
"[CONCEPT] appears in both [MATERIAL_A] and [MATERIAL_B]. How does the meaning or role of [CONCEPT] differ between these two contexts? Where do they overlap?"
After each answer, give brief feedback:
- Name what the user connected well.
- Name any distinction they missed (without lecturing — one sentence).
Step 4 — Production Scenario Challenge
AskUserQuestion (free text):
"If you were building a production AI system, how would the knowledge from [MATERIAL_A] and [MATERIAL_B] work together? Give a concrete scenario with specific design decisions."
Evaluate for:
- Coherence — does the scenario make technical sense?
- Specificity — are there real design decisions, not just buzzwords?
- Correct use of concepts — are terms from both materials used accurately?
Step 5 — Summary
Display:
Synthesis session complete.
Materials covered: [list]
Conceptual bridges built well: [list]
Bridges that need reinforcement: [list]
Send to Notion
Send to the Notion page of the most recent phase studied:
~/go/bin/notion-cli append --page-id PHASE_PAGE_ID --content "MARKDOWN"
Include:
- Cross-material concepts explored
- Gaps identified (bridges that need reinforcement)
- The production scenario the user described
Save Memory
Append to today's conversation log:
[HH:MM] synthesis session
Materials: [list] | Bridges built: N | Needs reinforcement: [list]
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install algernon-synthesis - After installation, invoke the skill by name or use
/algernon-synthesis - Provide required inputs per the skill's parameter spec and get structured output
What is Algernon Synthesis?
Cross-material knowledge synthesis session for OpenAlgernon. Use when the user runs `/algernon synthesis`, says "quero conectar os materiais", "sintese entre... It is an AI Agent Skill for Claude Code / OpenClaw, with 203 downloads so far.
How do I install Algernon Synthesis?
Run "/install algernon-synthesis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Algernon Synthesis free?
Yes, Algernon Synthesis is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Algernon Synthesis support?
Algernon Synthesis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Algernon Synthesis?
It is built and maintained by Antonio V. Franco (@antoniovfranco); the current version is v1.0.0.