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/memory-searchnpx skills add aksika/abtars --skill memory-searchgit 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/memory-search)<a href="https://agentmods.dev/skills/aksika/abtars/memory-search"><img src="https://agentmods.dev/badge/skills/aksika/abtars/memory-search.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 | $0.00014 | $0.00526 |
| Opus 5 | $0.00007 | $0.00263 |
| Sonnet 5 | $0.00003 | $0.00105 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
memory-search 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 5d 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
Memory Search
Full documentation for abmind recall. See TOOLS.md for quick reference.
abmind recall --translated "kw1,kw2" --chat-id 7773842843 [--original "szó"] [--time-start <ms>] [--time-end <ms>] [--max-classification 0-2] [--stages S1,S3] [--entity "Name"]
Parameter rules
--translated: ALWAYS English keywords. Translate the user's words to English.--original: If the user spoke in a non-English language, pass the original keyword here. Omit if the conversation is in English. Example: user says "chien" →--translated "dog" --original "chien"--stages: Optional. Run only specific stages (S1-S7, Se). Omit to run all.--entity: Optional. Filter results to memories linked to a specific entity (person, agent, project). Example: "what do you know about Alice?" →--entity "Alice"- Legacy:
--keywordsis accepted as alias for--translated.
Keyword rules
- Use English content words for --translated, NOT meta-words ("recent", "last session")
- For vague queries ("what did we talk about?"): use
"summary,discussion,update,decision"+--time-start24-48h ago - DB uses FTS5 — only actual content matches
Classification in context
--max-classification 0: group chats, A2A (UNCLASSIFIED only)--max-classification 2: direct messages (default, up to CONFIDENTIAL)- SECRET (3) always excluded
Expand source messages
abmind expand --ids 451,452,453
Use when results have source_ids and you need original context or "when did I say that?"
When to use
- User's message doesn't make sense in current context
- User asks to recall: "do you remember", "emlékszel", "what did we talk about"
- User references past topic/person/event not in current conversation
When NOT to use
- Short confirmations ("yes", "ok", "do it")
- Current context already explains the message
- User giving clear new instructions
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.
- 5d ago First seen · 49 lines · 14 tokens per session scan A 8d0275f19a0a
memory-search is a skill published in the GitHub repository aksika/abtars (9 stars, last pushed today), licensed Apache-2.0. It adds 14 tokens to every session and 526 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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