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-link/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-link)<a href="https://agentmods.dev/skills/ribeirogab/zeno-agent/memex-link"><img src="https://agentmods.dev/badge/skills/ribeirogab/zeno-agent/memex-link.svg" alt="Measured on agentmods" 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 | $0.00103 | $0.01140 |
| Opus 5 | $0.00051 | $0.00570 |
| Sonnet 5 | $0.00021 | $0.00228 |
| Haiku 4.5 | $0.00010 | $0.00114 |
Grade A, and why
memex-link scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memex Link — Vault Cross-Link Suggestions
Analyze the .vault/ vault and surface candidate related: frontmatter additions where genuinely necessary.
Announce at start: "Analyzing vault for missing cross-links..."
Mode of Operation
Four phases. Detection is deterministic (Bash). Presentation and editing are interactive (agent + user).
- Detect — invoke
scripts/find-candidates.sh "$SCOPE"(where$SCOPEis the optional argument from the slash command). - Classify — read JSON from stdout; map
evidence_typeto confidence (high/medium). - Present — render markdown table grouped by confidence, with one-line rationale.
- Loop — interactive y/n/skip-rest per item; on
y, edit source'srelated:frontmatter to add the wikilink.
If no candidates surface, say No cross-link suggestions. Vault is well-connected. and stop.
Phase 1 — Detect
Sanity-check command -v jq first — if absent, abort with memex-link requires jq. Install with: brew install jq (or platform-appropriate hint).
Then run the deterministic detector:
SCOPE="$1" # optional argument from slash command
SKILL_DIR="$(cd "$(dirname "${BASH_SOURCE[0]:-$0}")" && pwd)"
bash "$SKILL_DIR/scripts/find-candidates.sh" "$SCOPE" > /tmp/memex-link-candidates.json
If the script exits with code 2, surface its stderr and stop. If exit 0 and stdout is [], report "Vault is well-connected" and stop.
Phase 2 — Classify
For each candidate, map evidence_type to confidence:
evidence_type |
Confidence |
|---|---|
wikilink_in_body |
high |
filepath_in_body |
medium |
title_in_body |
medium |
shared_heading_terms |
medium |
No "low" bucket; the script does not emit anything that would qualify.
Phase 3 — Present
Render a markdown table grouped by confidence:
## Cross-Link Suggestions — N candidates (H high, M medium)
| # | conf | source → target | rationale |
|---|---|---|---|
| 1 | high | spec-rename… → memex | wikilink in body line 14 |
| 2 | medium | sweep → mechanical-enforcement-over-prose | shared H2 terms: feedforward, feedback |
What ships with it
16 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.
- scripts/find-candidates.sh 8.7 KB runs code
- tests/expected-output.json 1.7 KB
- tests/fixtures/vault/learnings/already-cited-target.md 186 B
- tests/fixtures/vault/learnings/already-citing-source.md 244 B
- tests/fixtures/vault/learnings/source-shared-headings-A.md 139 B
- tests/fixtures/vault/learnings/source-shared-headings-B.md 139 B
- tests/fixtures/vault/learnings/source-with-filepath.md 179 B
- tests/fixtures/vault/learnings/source-with-title-mention.md 230 B
- tests/fixtures/vault/learnings/source-with-wikilink.md 178 B
- tests/fixtures/vault/learnings/target-distinctive-phrase-title.md 133 B
- tests/fixtures/vault/learnings/target-of-wikilink.md 147 B
- tests/fixtures/vault/learnings/target-with-filepath.md 97 B
- tests/fixtures/vault/specs/2026-01-01-test-spec/plan-test-spec.md 107 B
- tests/fixtures/vault/specs/2026-01-01-test-spec/spec-test-spec.md 212 B
- tests/fixtures/vault/specs/2026-01-01-test-spec/tasks-test-spec.md 136 B
- tests/run.sh 500 B runs code
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.
- 8d ago First seen · 109 lines · 103 tokens per session scan A 372b58e3e9ed
memex-link is a skill published in the GitHub repository ribeirogab/zeno-agent (9 stars, last pushed 3mo ago), licensed MIT. It adds 103 tokens to every session and 1,140 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
hive.context-preservation
Proactively extract critical values from tool results into working notes before automatic context pruning destroys them.
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.
caveman-compress
Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or…
continuous-learning-v2
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
lat-md-knowledge-graph
Design or audit a repo-local markdown knowledge graph with wiki links, source-code backlinks, drift checks, and searchable sections. Use when AGENTS.md/CLAUDE.md is too flat for a large codebase or when a custom harness needs durable structured project memory.
dream
Prunes and consolidates the project's auto-memory to keep it minimal — deletes stale, wrong, or redundant memories, merges overlapping ones into existing files, and trims the index. Strong bias against growth: never creates new memory files and never stores new facts. Verifies staleness against the current codebase…