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SKILL verified MIT Self-run

Wiki Context Pack

skill-ar9av-obsidian-wiki-wiki-context-pack · by Ar9av

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Install

$ agentstack add skill-ar9av-obsidian-wiki-wiki-context-pack

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Wiki Context Pack — Bounded Token Retrieval

You are producing a focused, token-bounded context pack from the wiki. Unlike wiki-query (which answers a question), this skill packages the most relevant wiki knowledge into a single markdown block that a downstream agent, skill, or user can consume directly.

Before You Start

  1. Resolve config — follow the Config Resolution Protocol in llm-wiki/SKILL.md (walk up CWD for .env~/.obsidian-wiki/config → prompt setup). This gives OBSIDIAN_VAULT_PATH and any QMD variables.
  2. Read $OBSIDIAN_VAULT_PATH/hot.md if it exists — gives instant context on recent activity.
  3. Read $OBSIDIAN_VAULT_PATH/index.md — the full page inventory.

Invocation Forms

/wiki-context-pack "transformer attention mechanism" --budget 16000
/wiki-context-pack "my-project architecture decisions" --budget 8000
/wiki-context-pack --recent --budget 4000   # recent activity pack from hot.md
/wiki-context-pack "authentication patterns"          # default budget: 8000 tokens

Parse the user's invocation to extract:

  • topic — the query string (required unless --recent)
  • --budget N — token budget in tokens (default: 8000; max: 100000)
  • --recent — pack the most recently updated/ingested pages instead of a topic query

Algorithm

Step 1: Relevance Pass (cheap)

Without opening page bodies:

  1. Scan index.md and frontmatter for topic match. Score each page:
  • +5 exact title or alias match
  • +3 tag match
  • +2 summary: field contains the query term
  • +1 index.md entry description contains the query term
  1. For --recent mode: sort pages by updated: frontmatter descending. Take top 20 as candidates.
  1. For topic mode: collect the top 20 candidates by score. If QMD is configured (QMD_WIKI_COLLECTION set), run a semantic pass and merge with the frontmatter score (QMD rank adds +4 to the page's score).

Step 2: Tier-Aware Selection

Within the candidate set, sort by relevance score, then apply tier ordering within each score bucket (see llm-wiki/SKILL.md, Importance Tiering section):

  1. All core-tier matches first
  2. Then supporting
  3. Then peripheral (only if budget allows)

Maintain this ordering when filling the budget in Step 3.

Step 3: Compression

For each selected page (in tier/relevance order), compute its compressed representation — not a full read, but a structured distillation:

  1. Required: title, tier:, tags:, summary: (from frontmatter — cheap, no body read needed)
  2. If budget allows: add the page body, but stripped of:
  • Frontmatter block (already captured above)
  • The ## Sources section (keep source names in a one-liner instead)
  • Duplicate wikilinks that are already mentioned in included pages
  • Boilerplate headers with no content following them
  1. Dedup overlapping content — if two selected pages share a paragraph (or near-identical claim), keep it only in the more relevant page. Mark the removal: _(content also in [[other-page]])_.

Estimate tokens for each page representation as len(text_chars) / 4.

Step 4: Budget Enforcement

Fill the pack greedily in tier/relevance order until the budget is exhausted:

  1. Always include the frontmatter summary block for every selected page, even if the body doesn't fit.
  2. If a page body doesn't fit in full, include a compressed excerpt: the first non-header paragraph plus the "Key Ideas" section (if present).
  3. Drop peripheral-tier pages first when trimming.
  4. Keep a running token count. Stop adding pages when the next page would exceed the budget.
  5. Track how many pages were dropped and note it in the header.

Step 5: Render Output

Emit a single markdown block:

# Context Pack: 
# Generated: 
# Budget:  tokens | Actual:  tokens | Pages:  / 
# Methodology: 4 chars/token estimate

---

## [[]] (, ~ tokens)
tags: #tag1 #tag2
summary: 

---

## [[]] (, ~ tokens)
...

If --recent mode, the header reads:

# Context Pack: Recent Activity (last N pages)

Empty result: If no pages scored above 0 and --recent produced no results, output:

# Context Pack: 
No relevant pages found. Consider running /wiki-ingest to add sources about this topic.

Step 6: Log

Append to $OBSIDIAN_VAULT_PATH/log.md:

- [TIMESTAMP] CONTEXT_PACK topic="" budget= actual_tokens= pages_included= pages_dropped=

Use Cases

  • Feed into /wiki-research — pass the pack as context to avoid re-discovering known facts
  • Pass to /wiki-synthesize — scoped input for a specific synthesis task
  • Provide to external agents via MCP or clipboard — bounded, structured, citation-ready
  • Checkpoint context before a long multi-step task — know what the wiki already knows before starting

Notes

  • The 4 chars/token heuristic matches wiki-status's token footprint estimate — consistent across skills
  • The pack is a snapshot; it is not written to the vault. Re-run to refresh.
  • For very large budgets (> 50K tokens), warn the user: "This pack is large. Consider narrowing your topic or using wiki-query for a targeted answer instead."

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.