Borrowing it
Nothing to install: this file belongs to ribeirogab/zeno-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ribeirogab/zeno-agent/main/.agents/skills/memex-recall/SKILL.mdgit clone --depth 1 https://github.com/ribeirogab/zeno-agentWrote 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/ribeirogab/zeno-agent/memex-recall)<a href="https://agentmods.dev/skills/ribeirogab/zeno-agent/memex-recall"><img src="https://agentmods.dev/badge/skills/ribeirogab/zeno-agent/memex-recall/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/ribeirogab/zeno-agent/memex-recall"><img src="https://agentmods.dev/badge/skills/ribeirogab/zeno-agent/memex-recall.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 | $0.00013 | $0.00346 |
| Opus 5.5 | $0.00005 | $0.00138 |
| Sonnet 5.5 | $0.00003 | $0.00069 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
memex-recall 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
Recall — Project Context Scout
Quick reconnaissance of the .vault/ vault. Gives the agent a working map of where things are and what the project cares about, without deep-diving into every file.
Announce at start: "Running project reconnaissance..."
Protocol
Execute these steps in order. Read files — do not edit anything.
1. Structure scan
Run a glob for .vault/**/*.md to get the file tree. Present it as a compact list grouped by folder.
2. Constitution (skim)
Read .vault/constitution.md. Extract and list:
- The "Why" summary (1-2 sentences)
- Scope guardrails (bullet list)
- Architecture principles (bullet list)
3. MOCs (index scan)
Read all files in .vault/_index/. For each MOC, list the entries it links to (just the note names, not full content).
4. Report
Output a single structured summary:
Project Recon
What: Stack:
Knowledge Map
- Constitution: principles
- Specs: shipped, active
- Learnings: notes —
- Conventions: notes —
- Rules: notes
Key Pointers
Keep the whole output under 40 lines. This is a map, not a book report.
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 · 51 lines · 13 tokens per session scan A 0635a687d0d9
memex-recall is a skill published in the GitHub repository ribeirogab/zeno-agent (10 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 346 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 2026-08-31.
Other skills, from other repositories
weekly-digests
Generate a serial week-by-week narrative digest of a project's full claude-mem timeline. Splits the timeline into per-ISO-week files, then runs one consecutive subagent per week — each receiving the prior week's carry-forward block — to produce one chapter per ISO week of data. Use when asked for "weekly digests"…
cloud-sync
Set up or check claude-mem cloud sync with cmem.ai Pro. Use when the user says "set up cloud sync", "sync my memories", "cmem pro", "cloud backup", "sync status", or wants their memory database backed up or synced to their cmem.ai account.
screenpipe
Search screen and audio history recorded by Screenpipe and optionally save selected context into claude-mem. Use when the user asks to recall desktop activity, a meeting, or something seen in another app through Screenpipe.
emerging-techniques-long-context
Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers rotary embeddings, attention biases…
forget
Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely…
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.