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 skills/aksika/abtars/topic-savenpx skills add aksika/abtars --skill topic-savegit clone --depth 1 https://github.com/aksika/abtarsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aksika/abtars/topic-save)<a href="https://agentmods.dev/skills/aksika/abtars/topic-save"><img src="https://agentmods.dev/badge/skills/aksika/abtars/topic-save.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00012 | $0.00326 |
| Opus 5 | $0.00006 | $0.00163 |
| Sonnet 5 | $0.00002 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00033 |
Grade A, and why
topic-save 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 3d 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.
What it actually says
Topic Save
Save topic-specific knowledge from conversations into persistent markdown files at ~/.abtars/workspace/topics/.
How to invoke
Use native file tools (read/write/list directory). No CLI commands.
- Sanitize name: spaces→hyphens, remove non-alphanumeric (keep
-_), collapse consecutive hyphens, preserve casing. Reject if empty or contains..or starts with/. - Check existing: list
~/.abtars/workspace/topics/, case-insensitive match on{Name}-*.md. If found, update that file. If multiple, use most recent date. - Create new: write to
~/.abtars/workspace/topics/{Name}-{YYYY-MM-DD}.md - Update existing: read file, append/merge new content into relevant sections, write back. Keep original filename/date.
File format
# {TopicName}
## Summary
[Condensed summary]
## Key Points
- [Point 1]
- [Point 2]
## Details
[Expanded details by subtopic]
Write condensed summaries, not transcript dumps.
When to use
- User says "save this topic", "store this as a topic", "add this to the X topic"
When NOT to use
- Routine messages, greetings, small talk
- Short facts/preferences (use instant-store)
- Recall/search requests (use memory-search)
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.
- 3d ago First seen · 45 lines · 12 tokens per session scan A 48d53bbc2f1b
topic-save is a skill published in the GitHub repository aksika/abtars (9 stars, last pushed 3d ago), licensed Apache-2.0. It adds 12 tokens to every session and 326 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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