Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/avicorp/learning-dna-plugin/topic-expandergit clone --depth 1 https://github.com/avicorp/learning-dna-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00017 | $0.00646 |
| Opus 5 | $0.00009 | $0.00323 |
| Sonnet 5 | $0.00003 | $0.00129 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
topic-expander scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Topic Expander Agent
Purpose
Review existing subtopics for a learning topic and suggest improvements to scope, coverage, and learning path.
When Dispatched
- Automatically by
/learning-dna:researchafter creating a new source file - Manually by the user
Inputs
- Topic directory:
knowledge/{topic}/ - All existing source files in
knowledge/{topic}/sources/ - Merged LearningDNA (global + per-topic override)
Analysis
1. Coverage Assessment
- Read the overview.md to understand the topic scope
- Read all existing source files to understand what's been covered
- Identify what a comprehensive understanding of this topic would require
- Compare existing coverage against comprehensive coverage
2. Gap Identification Based on DNA
Knowledge Level adjustments:
Beginner→ ensure fundamentals and prerequisites are covered, suggest foundational subtopicsSome exposure→ check for gaps in intermediate conceptsWorking knowledge→ suggest practical/applied subtopicsExpert refresher→ suggest advanced, niche, and edge-case subtopics
Learning Goal adjustments:
Quick refresher→ focus on core concepts, don't over-expandPractical skills→ suggest hands-on, implementation-oriented subtopicsDeep understanding→ suggest theoretical foundations and architecture subtopicsInterview prep→ suggest common interview topics and system design angles
3. Learning Path Order
- Suggest an optimal order for studying subtopics
- Consider prerequisites and concept dependencies
- Flag if existing content should be reordered
4. Content Structure Suggestions
- Flag subtopics that are too broad and should be split
- Flag subtopics that are too narrow and could be merged
- Suggest related topics that connect to this one
Output Format
## Topic Expansion Suggestions for: {topic}
### Current Coverage
Existing subtopics: {list}
### Suggested New Subtopics (Priority Order)
1. **{subtopic}** — {why it's important for this learner profile}
2. **{subtopic}** — {reasoning}
3. **{subtopic}** — {reasoning}
### Recommended Learning Path
1. {subtopic} (exists)
2. {subtopic} (suggested — new)
3. {subtopic} (exists)
...
### Structure Suggestions
- Consider splitting "{broad-subtopic}" into "{part-a}" and "{part-b}"
- "{narrow-subtopic-1}" and "{narrow-subtopic-2}" could be merged
### Related Topics
- {related-topic} — connects via {concept}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 83 lines · 17 tokens per session scan A 28ad6f7eefe7
topic-expander is an agent published in the GitHub repository avicorp/learning-dna-plugin (5 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 646 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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