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logseq-wiki: Skill for Claude Code

.skills/wiki-context-pack/SKILL.md

wiki-context-pack is a skill for Claude Code, Codex from ystreibel/logseq-wiki. It costs 94 tokens per session (1,322 once invoked), scanned A, original, MIT.

A limited-size collection of the most relevant pages from a Logseq wiki, a collection of linked Markdown notes. It prepares focused background information about a topic or recent activity.

In plain words
What is it for?
Use it to package context for a topic, a specific page, or recent changes. You can set a maximum size in tokens, which are units used to measure text for language models.
Why use it?
It gives another coding agent or task the useful context it needs without passing along the entire wiki.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

This is ystreibel/logseq-wiki's own configuration. It tells Claude Code and Codex how to work on logseq-wiki itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything logseq-wiki configures →

not rated 5repo 11d ago A scan 94 tokens original MIT
View source ↗ ystreibel/logseq-wiki
Reuse

Borrowing it

Nothing to install: this file belongs to ystreibel/logseq-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ystreibel/logseq-wiki/main/.skills/wiki-context-pack/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/ystreibel/logseq-wiki

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for wiki-context-pack

README.md
[![agentmods](https://agentmods.dev/badge/skills/ystreibel/logseq-wiki/wiki-context-pack/github.svg)](https://agentmods.dev/skills/ystreibel/logseq-wiki/wiki-context-pack)
Your own site
<a href="https://agentmods.dev/skills/ystreibel/logseq-wiki/wiki-context-pack"><img src="https://agentmods.dev/badge/skills/ystreibel/logseq-wiki/wiki-context-pack/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.

agentmods 80×15 button for wiki-context-pack

Your own site · 80×15
<a href="https://agentmods.dev/skills/ystreibel/logseq-wiki/wiki-context-pack"><img src="https://agentmods.dev/badge/skills/ystreibel/logseq-wiki/wiki-context-pack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,322 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.01322
Opus 5.5 $0.00038 $0.00529
Sonnet 5.5 $0.00019 $0.00264
Haiku 4.5 $0.00009 $0.00132

Measured 2mo ago against content hash 91651f8284a2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

wiki-context-pack 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 2mo 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.

.skills/wiki-context-pack/SKILL.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Logseq Context Pack — Agrégation de Contexte Bounded

Ce skill produit un condensé structuré et limité en jetons du savoir contenu dans le wiki pour nourrir un autre agent, un sous-agent ou une tâche d'implémentation spécifique.

Avant de commencer

  1. Résoudre la configuration : Charger .env ou ~/.logseq-wiki/config pour obtenir LOGSEQ_VAULT_PATH.
  2. Lire wiki/_master-index.md pour connaître l'inventaire des pages physiques.
  3. Lire wiki/hot.md si présent pour le contexte récent.

Formes d'invocation

/wiki-context-pack "concepts/attention-mechanism" --budget 16000
/wiki-context-pack "mon-projet architecture" --budget 8000
/wiki-context-pack --recent --budget 4000
/wiki-context-pack "pattern auth"            # budget par défaut : 8000 tokens

Paramètres :

  • topic : Terme ou page cible à packager.
  • --budget N : Budget maximum en tokens (défaut : 8000, max : 100000).
  • --recent : Packager l'activité récente (pages triées par updated:: descendant).

Algorithme de Packaging

Étape 1 : Calcul de pertinence (léger)

  1. Parcourir l'index et les propriétés en tête de fichier pour attribuer un score de pertinence :
    • +5 : Match exact avec le titre ou un alias.
    • +3 : Présence du tag recherché.
    • +2 : Présence du terme dans la propriété summary::.
  2. En mode --recent : Prendre les 20 pages wiki les plus récemment mises à jour (updated::).
  3. En mode thématique : Sélectionner les 20 meilleures pages selon le score.

Étape 2 : Filtrage par Tiers (Importance Tiering)

Trier les 20 candidats selon leur score de pertinence, puis par tier (selon tier:: défini dans llm-wiki/SKILL.md) :

  1. Pages tier:: core en premier.
  2. Pages tier:: supporting ensuite.
  3. Pages tier:: peripheral en dernier.

Étape 3 : Compression du contenu

Pour chaque page sélectionnée, générer sa représentation compressée :

  1. Obligatoire : titre, tier::, tags::, summary:: (très économique, issu des premières lignes).
  2. Si le budget restant le permet : ajouter le corps de la page dépouillé de :
    • Son bloc de propriétés head (déjà lu ci-dessus).
    • Sa section ## Liens ou ## Sources (qui sera résumée sur une ligne).
    • Les puces redondantes avec d'autres pages déjà intégrées.
  3. Estimer la taille en tokens : caractères / 4.

Read the full file on GitHub · 114 lines

Changes

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.

  1. 2mo ago First seen · 114 lines · 94 tokens per session scan A 91651f8284a2

Subscribe to this mod's changes

wiki-context-pack is a skill published in the GitHub repository ystreibel/logseq-wiki (5 stars, last pushed 11d ago), licensed MIT. It adds 94 tokens to every session and 1,322 once invoked, about $0.0004 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.

Memory and context
Related

wiki-context-pack compared with skills from other repositories

wiki-context-pack next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
wiki-context-packystreibel/logseq-wikiSkill511d agoMITA94Claude Code, Codex
knowledge-ingestopenclaw/openclawSkill394ktodayMITA80Claude Code, Codex
mem0-oss-to-platformmem0ai/mem0Skill68k2d agoApache-2.0A217Claude Code, Codex
forgetasgeirtj/system_prompts_leaksSkill71k2d agoCC0-1.0A74Claude Code, Codex
Cortexdanielmiessler/LifeOSSkill20kyesterdayMITA184Claude Code
ha-data-storesshiwenwen/hope-agentSkill1.9kyesterdayMITA115Claude Code, Codex
memoryopensquilla/opensquillaSkill7.1k6d agoApache-2.0A44Claude Code, Codex