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/sdsrss/claude-mem-liteWrote 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/sdsrss/claude-mem-lite/memory)<a href="https://agentmods.dev/commands/sdsrss/claude-mem-lite/memory"><img src="https://agentmods.dev/badge/commands/sdsrss/claude-mem-lite/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/sdsrss/claude-mem-lite/memory"><img src="https://agentmods.dev/badge/commands/sdsrss/claude-mem-lite/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 | $0.00025 | $0.00433 |
| Opus 5.5 | $0.00010 | $0.00173 |
| Sonnet 5.5 | $0.00005 | $0.00087 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
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 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
Memory Save
Save important content to your long-term memory database.
Commands
/claude-mem-lite:memory <content>— Save the given content directly to memory/claude-mem-lite:memory(no args) — Auto-summarize recent session highlights and save key findings
Instructions
When the user invokes /claude-mem-lite:memory, determine the intent:
With explicit content
If the user provides content after the command:
- Analyze the content to determine appropriate type (decision, bugfix, feature, refactor, discovery, change)
- Generate a concise title from the content
- Call
mem_savewith:content: the provided texttitle: auto-generated titletype: inferred type (default: "discovery")importance: 2 (notable — user explicitly requested save)
With instructions/prompt
If the user provides instructions like "save the database schema we discussed" or "remember the fix for the auth bug":
- Review recent conversation context
- Extract the relevant information per the user's instruction
- Call
mem_savewith extracted content, appropriate title and type, importance=2
No arguments (auto-save)
If no content is provided:
- Review the current session's recent key findings
- Identify: decisions made, bugs fixed, patterns discovered, important code changes
- For each significant finding (max 5), call
mem_savewith:- Clear title and structured content
- Appropriate type and importance level (1=routine, 2=notable)
- Skip trivial or already-saved items
- Report what was saved in a concise summary
Always set importance=2 for explicit saves (user chose to save), importance=1 for auto-saves of routine items, importance=2 for auto-saves of notable discoveries.
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 Changed 0aece732ff36
- 1mo ago First seen · 52 lines · 25 tokens per session scan A 5c7d0fb0c50f
memory is a command published in the GitHub repository sdsrss/claude-mem-lite (67 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 433 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
session-save
Save the current session state — decisions, modified files, current status, and next steps — to a handoff file for later resume.
drift-detect
Configuration drift detection command. Finds inconsistencies, orphaned components, and stale content in the Badi system.
wrap-up
End-of-day ritual command. Prepares the day for closure and sets the stage for tomorrow.
clear
Context-clearing command. Provides a seamless transition across session boundaries. Target: under 30 seconds.
sync
Mid-session context refresh command. Keeps context fresh and consistent during work.
memory-diff
Memory and knowledge-base limit check + global project comparison.