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.
git clone --depth 1 https://github.com/Markgatcha/memosWrote 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/commands/markgatcha/memos/recall)<a href="https://agentmods.dev/commands/markgatcha/memos/recall"><img src="https://agentmods.dev/badge/commands/markgatcha/memos/recall/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/markgatcha/memos/recall"><img src="https://agentmods.dev/badge/commands/markgatcha/memos/recall.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00015 | $0.00150 |
| Opus 5 | $0.00008 | $0.00075 |
| Sonnet 5 | $0.00003 | $0.00030 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
recall 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
Recall memories relevant to: $ARGUMENTS
- Call
memos_context_packwithqueryset to "$ARGUMENTS" andtokenBudget2000. If the result looks sparse, widen withmemos_search(limit 10). - Summarize what the memories say in plain prose, citing memory IDs like
[mem:abc12345]for anything I might want to update or forget. - If nothing relevant exists, say so plainly and offer to
memos_storea new memory if I state the fact now.
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 · 11 lines · 15 tokens per session scan A f9398705184b
recall is a command published in the GitHub repository Markgatcha/memos (6 stars, last pushed 4d ago), licensed MIT. It adds 15 tokens to every session and 150 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 2026-09-08.
Other commands, from other repositories
pensyve
Route explicit Pensyve memory requests through the bundled MCP server; supports recall, remember, observe, inspect, status, review, forget, and mention-style guidance.
recall
Search Pensyve memory by semantic similarity and text matching.
using-pensyve
Show available Pensyve memory tools, skills, and commands.
consolidate
Run memory consolidation to promote, decay, and archive memories.
forget
Delete all memories for an entity from Pensyve.
inspect
View all memories stored for an entity in Pensyve.