Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/linxule/memex-pluginnpx agentmods add skills/linxule/memex-plugin/garden-tendingWrote 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/skills/linxule/memex-plugin/garden-tending)<a href="https://agentmods.dev/skills/linxule/memex-plugin/garden-tending"><img src="https://agentmods.dev/badge/skills/linxule/memex-plugin/garden-tending/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/skills/linxule/memex-plugin/garden-tending"><img src="https://agentmods.dev/badge/skills/linxule/memex-plugin/garden-tending.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00131 | $0.13370 |
| Opus 5.5 | $0.00052 | $0.05348 |
| Sonnet 5.5 | $0.00026 | $0.02674 |
| Haiku 4.5 | $0.00013 | $0.01337 |
Grade A, and why
garden-tending scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 964 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Portable copy of
skills/garden-tending/SKILL.mdfor Codex and Kimi Code, generated byscripts/portable_plugin.py(do not edit here). Needs thememexCLI on PATH. Claude Code names (the Task/Agent tool,/memex:save, hooks) map to your host's equivalents.
Knowledge Garden Tending
Current State
Index: (run: sqlite3 "$(memex path --index 2>/dev/null)" "SELECT (SELECT COUNT(*) FROM fts_content) || ' docs, ' || (SELECT COUNT(*) FROM chunks) || ' chunks indexed'" 2>/dev/null || echo "(index unavailable)")
Condensation backlog (projects whose overview lags their memos — dated after condensed:, or more memos than memos_digested:):
(run: memex check --condense 2>/dev/null | head -30 || echo "(memex CLI unavailable)")
Topic signal backlog (open ## Recent signals; closed sections and archived/redirect topics excluded):
(run: memex check --signals 2>/dev/null | head -16 || echo "(memex CLI unavailable)")
Existing topics (use [[?name]] for anything NOT in this list):
(run: ls $(memex path 2>/dev/null)/topics/*.md 2>/dev/null | xargs -I{} basename {} .md | sort | tr '\n' ' ' || echo "(no topics found)")
Path Setup
The memex CLI handles vault path resolution automatically. For Obsidian CLI and dreamer commands not yet wrapped, prefix with cd $(memex path 2>/dev/null) &&.
Core Principle
Memos are ore. Project overviews are metal. Topics are the connective tissue. Trails are the narrative arc. The vault is a living knowledge graph, not an archive. Garden tending is the practice of keeping it alive: distilling memos into overviews, connecting ideas across projects, pruning dead links, growing new topics where patterns emerge, and extending trails where understanding evolves.
The test: if someone starts a session in this project tomorrow, does the vault give them enough to pick up where things left off?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 22d ago Changed · +1 lines ba6097361a6c
- 29d ago Changed · -10 lines 113c520d63a4
- 1mo ago Changed · +12 lines 335c255b4311
- 1mo ago First seen · 961 lines · 131 tokens per session scan A 15e898f4cdba
garden-tending is a skill published in the GitHub repository linxule/memex-plugin (7 stars, last pushed 2d ago), licensed MIT. It adds 131 tokens to every session and 13,370 once invoked, about $0.0005 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 skills, from other repositories
superbrain-distill
Internal SuperBrain skill — run by the detached capture child to distill a session-event delta into routed Obsidian notes. Not for direct user invocation.
superbrain-recall
Search the user's SuperBrain second-brain vault. Use whenever the user references past work, prior decisions, "how did we", "did we already", earlier sessions, a project's history, or anything that may already be recorded — before answering from scratch.
memento
Capture durable knowledge from the current work session into Memento Vault. Use when the user asks to remember, save, capture, or record decisions, discoveries, bug fixes, or reusable patterns.
inception
Run or preview Memento Vault consolidation. Use when the user asks to consolidate, find patterns, run inception, preview clusters, or synthesize cross-session themes.
concierge
Search Memento Vault for day-to-day recall, past decisions, discoveries, implementation history, and prior session context. Use when the user asks "do you remember", "have we seen", "what did we decide", "what did we learn", "where was this implemented", "find prior context", "check memory", "search the vault", or any…
continue-work
Use when the user says "continue", "pick up where I left off", "what was I working on", or similar. Also use when starting a session and memory has pending work.