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/noizu-labs-ml/NoizuPromptLingoWrote 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/noizu-labs-ml/noizupromptlingo/memory-compress)<a href="https://agentmods.dev/commands/noizu-labs-ml/noizupromptlingo/memory-compress"><img src="https://agentmods.dev/badge/commands/noizu-labs-ml/noizupromptlingo/memory-compress/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/noizu-labs-ml/noizupromptlingo/memory-compress"><img src="https://agentmods.dev/badge/commands/noizu-labs-ml/noizupromptlingo/memory-compress.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 | $0.00079 | $0.01148 |
| Opus 5 | $0.00039 | $0.00574 |
| Sonnet 5 | $0.00016 | $0.00230 |
| Haiku 4.5 | $0.00008 | $0.00115 |
Grade A, and why
memory-compress 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.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Compression
Maintenance pass over the persistent memory system at
<project-memory-dir>/MEMORY.md and its linked files. Goal: keep memory
small, current, and load-bearing — every line still in MEMORY.md after
this pass must earn its place in every future conversation's context.
This command does not change what gets saved during normal conversation (see the memory instructions in the system prompt for that). It only compacts what has already accumulated.
Procedure
-
Load the index. Read
MEMORY.mdin the current project's memory directory. If it doesn't exist or is empty, report that there's nothing to compress and stop. -
Read every linked file. For each
- [Title](file.md) — hookline, readfile.mdin full, including its frontmatter (name,description,metadata.type). -
Score each memory against these removal/merge criteria:
- Duplicate or overlapping — two files cover the same fact/rule with
only wording differences → merge into one, keep the clearer
Why/How to apply, delete the other, update its[[links]]references. - Superseded — a newer memory contradicts an older one (e.g. a
feedbackmemory that reverses an earlier one) → keep only the current version; delete the stale one rather than stacking corrections. - Expired
projectmemory — dates, deadlines, or "in-progress" state that has clearly passed relative to today's date, with no indication it's still relevant → delete. If the file and the current date, run a quick reality check first (see step 4). - Verifiable but unverified claims — a memory naming a specific file, function, flag, or config value that hasn't been checked recently enough to trust → do NOT delete solely for this; instead spot-check (step 4) and update or flag it.
- Over-verbose — correct and still relevant, but padded with restated context or hedging → rewrite tersely in place, don't delete.
- Never-referenced trivia — content that reads as a debugging recipe, code-pattern note, or something derivable by reading the repo (excluded categories per the memory system's own rules) → delete outright, it should never have been saved.
- Duplicate or overlapping — two files cover the same fact/rule with
only wording differences → merge into one, keep the clearer
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 · 90 lines · 79 tokens per session scan A 7c76f5c495e8
memory-compress is a command published in the GitHub repository noizu-labs-ml/NoizuPromptLingo (13 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 1,148 once invoked, about $0.0004 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 2026-09-04.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.