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/linggen/linggen-memoryWrote 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/linggen/linggen-memory/scan)<a href="https://agentmods.dev/commands/linggen/linggen-memory/scan"><img src="https://agentmods.dev/badge/commands/linggen/linggen-memory/scan/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/linggen/linggen-memory/scan"><img src="https://agentmods.dev/badge/commands/linggen/linggen-memory/scan.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 | $0.00011 | $0.00114 |
| Opus 5.5 | $0.00004 | $0.00046 |
| Sonnet 5.5 | $0.00002 | $0.00023 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
scan 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
Invoke the linggen skill (Skill tool) and treat this message as /linggen scan $ARGUMENTS — Scan mode. Follow the skill's Scan procedure (references/dream-flow.md, Scan section): run scripts/scan.sh for the given date, skip sessions already contributing to that day's rows, encode the remaining keepers into episodic, then stamp with ling-mem harvest-day. A date argument is required.
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 · 7 lines · 11 tokens per session scan A 8d39621880be
scan is a command published in the GitHub repository linggen/linggen-memory (110 stars, last pushed 12d ago), licensed MIT. It adds 11 tokens to every session and 114 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 2026-08-30.
Other commands, from other repositories
bm
Ask basemind anything about the current codebase — outlines, refs, callers, git history, blame, diffs, docs, memory.
compress
Automatically compress CLAUDE.md or other memory files with protected-span safety. One-command token savings.
index
Full AI context and content layer for coding agents over one MCP server — tree-sitter code-map, document RAG, shared memory, multi-agent comms, web crawl, git history + blame. 300+ languages, 10+ agent harnesses, pure Rust.
learn
A command that saves reusable discoveries and lessons from a coding session as one-line JSON records. JSONL means one JSON object per line, making the file easy to append to and process.
oops
A command for immediately adding a documented mistake to a shared Markdown file. It records the recurring pattern, what happened, verifiable evidence, and a prevention step.
compact-ctx
A command for managing a coding session when its conversation history becomes large. It explains when to compact the context, start a new session, split work, or use another agent.