安全扫描（ClawHub）

• VirusTotal ：可疑
• OpenClaw ：可疑

OpenClaw 评估

The skill's purpose (synthesizing study materials) is plausible, but the runtime instructions reference hard-coded local paths and external tooling (sqlite DB, notion-cli, PHASE_PAGE_ID) without declaring them — a configuration and privilege mismatch that should be resolved before use.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Algernon Synthesis」。简介：Cross-material knowledge synthesis session for OpenAlgernon. Use when the user …。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/antoniovfranco/algernon-synthesis/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: algernon-synthesis
description: >
  Cross-material knowledge synthesis session for OpenAlgernon. Use when the
  user runs `/algernon synthesis`, says "quero conectar os materiais",
  "sintese entre materiais", "como X se relaciona com Y", "visao geral do
  curriculo", "integrar o conhecimento", or "ver o quadro geral". Requires at
  least 2 materials with reviewed cards. Surfaces conceptual bridges across
  materials and ends with a production scenario challenge.
---

# 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

```bash
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:
1. Coherence — does the scenario make technical sense?
2. Specificity — are there real design decisions, not just buzzwords?
3. 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:

```bash
~/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]
```