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/GRU-953/MTA_PluginWrote 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/gru-953/mta_plugin/export-memory)<a href="https://agentmods.dev/commands/gru-953/mta_plugin/export-memory"><img src="https://agentmods.dev/badge/commands/gru-953/mta_plugin/export-memory/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/gru-953/mta_plugin/export-memory"><img src="https://agentmods.dev/badge/commands/gru-953/mta_plugin/export-memory.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 | $0.00008 | $0.00121 |
| Opus 5.5 | $0.00003 | $0.00048 |
| Sonnet 5.5 | $0.00002 | $0.00024 |
| Haiku 4.5 | $0.00001 | $0.00012 |
Grade A, and why
export-memory 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 1mo 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
Export the project's memory as portable Markdown files.
Destination: $ARGUMENTS
Steps:
- If no destination was given, ask where to export (default: the current directory).
- Call
export_memorywith the destination (andprojectif named). - It copies
memory.md, the per-documentmemory/notes,graph.json, and the recall index (vectors.npz/.json) to the destination. Confirm what was written.
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.
- 1mo ago First seen · 15 lines · 8 tokens per session scan A 8566d42dfdc5
export-memory is a command published in the GitHub repository GRU-953/MTA_Plugin (1 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 121 once invoked, about $0.0000 per session on Opus 5.5. 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.
Other commands, from other repositories
handoff
Capture this session as a Throughline handoff so any agent can resume it cleanly.
context-save
Save project context, decisions, and progress for a later session.
context
A project-context command that manages a .context directory containing decision notes, session logs, and history. It helps keep a record of why changes were made across Git branches and commits.
kiro-steering-custom
Command "kiro-steering-custom" from gotalab/cc-sdd, covering kiro custom steering creation, workflow, available templates, steering principles and tool guidance.
save-session-learnings
Document session learnings to CLAUDE.md and AGENTS.md. Use after completing significant tasks, debugging sessions, or discovering project patterns.
memory-why
Show why a memory recall returned what it did -- BM25 vs vector vs hybrid provenance.