김경종
139 lines
5.8 KiB
Markdown
139 lines
5.8 KiB
Markdown
---
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name: wiki-context-pack
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description: >
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Produce a token-bounded context pack from the Obsidian wiki — a compact, structured slice of the most
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relevant pages for a topic or recent activity, designed for downstream consumption by another agent or skill.
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Use when the user says "/wiki-context-pack", "make a context pack", "give me a context slice for X",
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"pack the wiki for my agent", or "bounded context for Y". Different from wiki-query (which answers a
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question) — this produces reusable input material for a downstream task.
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---
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# Wiki Context Pack — Bounded Token Retrieval
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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.
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## Before You Start
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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.
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2. Read `$OBSIDIAN_VAULT_PATH/hot.md` if it exists — gives instant context on recent activity.
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3. Read `$OBSIDIAN_VAULT_PATH/index.md` — the full page inventory.
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## Invocation Forms
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```
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/wiki-context-pack "transformer attention mechanism" --budget 16000
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/wiki-context-pack "my-project architecture decisions" --budget 8000
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/wiki-context-pack --recent --budget 4000 # recent activity pack from hot.md
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/wiki-context-pack "authentication patterns" # default budget: 8000 tokens
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```
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Parse the user's invocation to extract:
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- **topic** — the query string (required unless `--recent`)
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- **`--budget N`** — token budget in tokens (default: `8000`; max: `100000`)
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- **`--recent`** — pack the most recently updated/ingested pages instead of a topic query
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## Algorithm
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### Step 1: Relevance Pass (cheap)
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Without opening page bodies:
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1. Scan `index.md` and frontmatter for topic match. Score each page:
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- **+5** exact title or alias match
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- **+3** tag match
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- **+2** `summary:` field contains the query term
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- **+1** `index.md` entry description contains the query term
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2. For `--recent` mode: sort pages by `updated:` frontmatter descending. Take top 20 as candidates.
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3. 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).
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### Step 2: Tier-Aware Selection
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Within the candidate set, sort by relevance score, then apply tier ordering within each score bucket (see `llm-wiki/SKILL.md`, Importance Tiering section):
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1. All `core`-tier matches first
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2. Then `supporting`
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3. Then `peripheral` (only if budget allows)
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Maintain this ordering when filling the budget in Step 3.
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### Step 3: Compression
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For each selected page (in tier/relevance order), compute its **compressed representation** — not a full read, but a structured distillation:
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1. **Required**: title, `tier:`, `tags:`, `summary:` (from frontmatter — cheap, no body read needed)
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2. **If budget allows**: add the page body, but stripped of:
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- Frontmatter block (already captured above)
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- The `## Sources` section (keep source names in a one-liner instead)
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- Duplicate wikilinks that are already mentioned in included pages
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- Boilerplate headers with no content following them
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3. **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]])_`.
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Estimate tokens for each page representation as `len(text_chars) / 4`.
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### Step 4: Budget Enforcement
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Fill the pack greedily in tier/relevance order until the budget is exhausted:
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1. Always include the frontmatter summary block for every selected page, even if the body doesn't fit.
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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).
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3. Drop `peripheral`-tier pages first when trimming.
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4. Keep a running token count. Stop adding pages when the next page would exceed the budget.
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5. Track how many pages were dropped and note it in the header.
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### Step 5: Render Output
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Emit a single markdown block:
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```markdown
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# Context Pack: <topic>
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# Generated: <ISO timestamp>
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# Budget: <budget> tokens | Actual: <actual> tokens | Pages: <N included> / <M candidates>
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# Methodology: 4 chars/token estimate
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---
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## [[<category/page-name>]] (<tier>, ~<tokens> tokens)
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tags: #tag1 #tag2
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summary: <summary field text>
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<compressed body or excerpt>
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---
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## [[<next-page>]] (<tier>, ~<tokens> tokens)
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...
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```
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If `--recent` mode, the header reads:
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```
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# Context Pack: Recent Activity (last N pages)
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```
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**Empty result:** If no pages scored above 0 and `--recent` produced no results, output:
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```
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# Context Pack: <topic>
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No relevant pages found. Consider running /wiki-ingest to add sources about this topic.
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```
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### Step 6: Log
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Append to `$OBSIDIAN_VAULT_PATH/log.md`:
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```
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- [TIMESTAMP] CONTEXT_PACK topic="<topic>" budget=<N> actual_tokens=<M> pages_included=<K> pages_dropped=<D>
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```
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## Use Cases
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- **Feed into `/wiki-research`** — pass the pack as context to avoid re-discovering known facts
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- **Pass to `/wiki-synthesize`** — scoped input for a specific synthesis task
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- **Provide to external agents via MCP or clipboard** — bounded, structured, citation-ready
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- **Checkpoint context before a long multi-step task** — know what the wiki already knows before starting
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## Notes
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- The `4 chars/token` heuristic matches `wiki-status`'s token footprint estimate — consistent across skills
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- The pack is a snapshot; it is not written to the vault. Re-run to refresh.
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- 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."
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