Borrowing it
Nothing to install: this file belongs to saski/arnesto. 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/saski/arnesto/main/.agents/skills/wiki-dashboard/SKILL.mdgit clone --depth 1 https://github.com/saski/arnestoWrote 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/saski/arnesto/wiki-dashboard)<a href="https://agentmods.dev/skills/saski/arnesto/wiki-dashboard"><img src="https://agentmods.dev/badge/skills/saski/arnesto/wiki-dashboard.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 | $0.00126 | $0.01505 |
| Opus 5 | $0.00063 | $0.00753 |
| Sonnet 5 | $0.00025 | $0.00301 |
| Haiku 4.5 | $0.00013 | $0.00151 |
Grade A, and why
wiki-dashboard 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 3d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Dashboard — Dynamic Vault Views
You are creating a .base file — an Obsidian Bases definition that turns vault frontmatter into a live, queryable view. The .base format is native to Obsidian 1.8+ and requires no plugins.
Before You Start
- Read
~/.obsidian-wiki/config(preferred) or.env(fallback) to getOBSIDIAN_VAULT_PATH - Read
$OBSIDIAN_VAULT_PATH/index.mdto understand what categories and pages exist - Ask the user what they want to view if not specified — what folder, tag, category, or date range?
What Obsidian Bases Can Do
.base files define database-style views over vault notes. Each file declares:
- Which notes to include — filtered by folder, tag, frontmatter property, or combination
- Which properties to show — any frontmatter field becomes a column
- What view type —
table,cards, orlist - Sort and group — by any property
- Computed columns — formulas using
file.*helpers and arithmetic
Embed a .base into any note with ![[MyBase.base]].
Step 1: Understand the Request
Determine:
- What to show — all pages in a category? Pages with a specific tag? A project's pages?
- What columns matter — title, tags, created, updated, summary, category, project?
- View type — table (default), cards (visual), or list (minimal)
- Sort order — by updated (default), created, title, or a custom property
- Any filters — date range, specific tags, folder scope
Step 2: Generate the .base File
The .base format is YAML. Here are the patterns you'll use:
Basic table — all pages in a category folder
filters:
- type: folder
folder: concepts
columns:
- property: file.name
title: Page
- property: tags
title: Tags
- property: summary
title: Summary
- property: updated
title: Updated
sort:
- property: updated
direction: desc
view: table
Filtered by tag
filters:
- type: tag
tag: "#machine-learning"
columns:
- property: file.name
title: Page
- property: category
title: Category
- property: summary
title: Summary
- property: created
title: Created
sort:
- property: created
direction: desc
view: table
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.
- 3d ago First seen · 184 lines · 126 tokens per session scan A dc5c1cc9fdf7
wiki-dashboard is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed today), licensed Unlicense. It adds 126 tokens to every session and 1,505 once invoked, about $0.0006 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 2026-09-03.
Other skills, from other repositories
immune
Hybrid adaptive memory: Cheatsheet (positive patterns pre-generation) and Immune (negative patterns post-generation) with Hot/Cold tiered auto-learning. Triggers on: "scan for errors", "immune scan", "check output quality", "antibody scan". NOT for PR review (use pr-review) or repo audits (use repo-sentinel).
usage-audit
Audit a Claude Code setup for token waste and context bloat. Checks MCP servers, CLAUDE.md, skills, and settings against bloat filters. Triggers on: "audit my context", "usage audit", "token audit", "context bloat". NOT for codebase audits.
brain-ingest
The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the brain CLI.
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
agentic-os
A design for running persistent specialist agents, commands, scripts, and file-based memory inside Codex. It keeps the setup in project files so it can continue across sessions.
memory-and-handoff
Two-mode skill: (1) session memory — load/persist durable workflow state under .cc10x/ (activeContext, patterns, progress) so context survives compaction; (2) handoff package — portable, secrets-redacted export for a coworker, different tool, or fresh non-cc10x session.