| name | paper-query |
| description | Hierarchically answer questions by querying the Obsidian wiki knowledge base. Trigger when the user asks a question about papers, concepts, or relationships stored in the wiki; requests a comparison between papers or methods; asks for a synthesis across multiple pages; or seeks analysis, connections, or summaries of ingested knowledge. Uses a tiered retrieval strategy: semantic overview first, then structured knowledge, then raw sources, then external augmentation as needed.
|
Paper Query Skill
Answer user questions through a layered, adaptive retrieval pipeline. Start with
high-level wiki structure, progressively deepen into raw sources only when the
question demands specificity, and optionally augment with external knowledge when
wiki coverage is incomplete.
Goal
Transform a user question into:
- A targeted, cited answer grounded in the most appropriate depth of evidence.
- A persisted query record under
queries/<topic>/ that preserves the refined
question and full answer for future user reference. No new wiki pages are created.
Retrieval Layers
Layer 1 Semantic Overview ──► index.md, directory structure, page titles
(always run) └─► Fast landscape mapping
Layer 2 Structured Knowledge ──► papers/<topic>/*.md, concepts/*.md
(selective) └─► Deep understanding of processed content
Layer 3 Raw Evidence ──► Clippings/*.md, Clippings/_processed/*.md
(conditional) └─► Exact quotes, numbers, citations
Layer 4 External Augmentation ──► LLM parametric knowledge, web search
(fallback) └─► Fill gaps, verify recency, broaden context
Constraint: Do not skip Layer 1. Every query begins there. All deeper layers are
invoked only if the preceding layer is insufficient.
Query Workflow
Phase 0: Classify the Question (Implicit)
Before opening any file, form a quick mental model of what the question likely needs:
| Question archetype | Likely required layers | Example |
|---|
| Navigation / inventory | L1 only | "What papers do we have on RLHF?" |
| Concept definition | L1 → L2 | "What is GRPO and how does it work?" |
| Paper summary | L1 → L2 | "Summarize the key idea of [[Paper X]]." |
| Fact / number / quote | L1 → L2 → L3 | "What exact F1 score did they report on GLUE?" |
| Comparison / trend | L1 → L2 → (L3) → L4 | "How does X compare to Y? Is there newer work?" |
| Contradiction / gap | L1 → L2 → L3 → L4 | "Why do these two papers disagree on Z?" |
This is a planning heuristic, not a rigid rule. Re-evaluate after each layer.
Phase 1: Semantic Overview (Layer 1) — ALWAYS
Goal: Build a mental map of where relevant knowledge lives without reading full pages.
- Read
index.md in full.
- Grep for keywords across
papers/, concepts/, and Clippings/
to discover pages whose titles or summaries match the query.
Deliberately exclude queries/ from all searches to avoid circular
contamination and model hallucination from prior answers.
- Scan directory listings (
papers/*, concepts/*, Clippings/*.md) for
relevant filenames.
- Compile a candidate list with one-line relevance notes:
- Relevant topic directories
- Relevant concept pages
- Relevant paper pages
- Relevant clipping filenames
Stop criterion for simple navigation questions:
If the user only asked "what do we have on X?" or "list papers about Y", answer
immediately from the candidate list with wikilinks. No further layers needed.
Phase 2: Structured Knowledge (Layer 2) — USUALLY
Goal: Understand the processed, summarized content of the wiki.
- Read every candidate page identified in Phase 1 in full.
- Start with concept pages (they provide shared definitions).
- Then read paper pages (they provide specific contributions and positioning).
- Transitive expansion: If a read page contains
[[...]] wikilinks that look
highly relevant, read those pages too.
- Build an internal evidence board: For each relevant page, note:
- Key claims
- Methods / architectures
- Experimental highlights (high-level)
- Positioning against other work
- Open questions or contradictions mentioned
Sufficiency check — ask yourself:
- Does the user’s question ask for a specific number, verbatim quote, or fine-grained
experimental detail that is NOT present in the paper/concept summary pages?
- Does the answer feel like a high-level synthesis that is already well-supported?
| If sufficient | Action |
|---|
| Yes — question is conceptual, comparative, or summary-level | Jump to Phase 5 (Synthesize). |
| No — needs exact evidence, quotes, or numbers | Proceed to Phase 3 (Raw Evidence). |
Phase 3: Raw Evidence (Layer 3) — CONDITIONAL
Goal: Retrieve precise facts, direct quotes, tables of results, or citations
from the original clipping text.
- Select target clippings from the candidate list (Phase 1) based on which
paper pages (Phase 2) seemed most relevant but lacked the needed granularity.
- Read the clipping(s) in full or use targeted search (
Grep) within the
clipping for specific terms (e.g., the metric name, dataset name, table caption).
- Extract verbatim evidence with attribution to the clipping filename.
Citation discipline for raw evidence:
- When citing a fact from a clipping, use both the clipping and the derived page:
[[Paper Page]] (source: Clippings/_processed/<Name>.md).
- Prefer clipping evidence only when the structured page omits the detail.
Sufficiency check:
- Did the clipping contain the needed fact?
- Is the wiki itself missing coverage of a relevant paper or concept entirely?
| If sufficient | Action |
|---|
| Yes — raw evidence fills the gap | Jump to Phase 5 (Synthesize). |
| No — the topic is absent, outdated, or too new in the wiki | Proceed to Phase 4 (External Augmentation). |
Phase 4: External Augmentation (Layer 4) — FALLBACK
Goal: Compensate for missing, stale, or incomplete wiki coverage.
When to activate:
- The wiki contains no relevant pages after Phase 1.
- The relevant pages are too old and the user asks about "latest" or "recent" work.
- The question is about a paper that exists in
Clippings/ but has not yet been
ingested into papers/ (rare — prefer ingesting first, but acceptable for quick answers).
- A contradiction in the wiki cannot be resolved internally.
Allowed augmentation sources:
- LLM parametric knowledge — for well-established background, standard definitions,
or widely known results. Blend it naturally; no special tag required.
- Web search (
SearchWeb, FetchURL) — for very recent papers, verification of
numbers, or finding authoritative sources outside the vault.
Transparency requirement:
Web-sourced claims must be explicitly labeled with [External: <URL>]. LLM
parametric knowledge does not need a special tag; blend it naturally into the
answer but prefer wiki-grounded evidence when available.
If external augmentation reveals a significant gap in the wiki, note it in the
answer and optionally suggest that the user ingest the missing source.
Phase 5: Synthesize the Answer
Compose a response that directly addresses the user's question.
Citation discipline:
- Every factual claim, comparison, or quoted insight must be attributed to its source
using Obsidian wikilinks:
[[Page Name]].
- If the source is a clipping rather than a processed page, cite it as
Clippings/<Name>.md or Clippings/_processed/<Name>.md.
- If multiple pages support a single point, cite all of them.
- If the wiki contains conflicting information, present both sides and note the
contradiction explicitly.
Answer structure (adapt to the question):
- Direct answer: Start with a concise 1–3 sentence summary.
- Reasoning / evidence: Expand with evidence, grouped by theme or paper.
- Use headings or bullet points to separate layers of evidence if helpful.
- Sources section listing all pages and clippings consulted.
Phase 6: Persist the Query Record
Every query must be archived as a read-only record under queries/.
Isolation rule: Query records are user-managed archives. They are saved to
queries/ but are never referenced in index.md or log.md, and they are
excluded from all future retrieval layers.
-
Determine the topic folder:
- Look at the primary topic of the consulted papers/concepts.
- Use the same canonical topic slugs as
paper-injest:
video-generation, image-generation, language-model,
reinforcement-learning, vision, multimodal, inference-optimization,
training-systems, efficiency, alignment.
- If the query spans multiple topics, pick the dominant one or use
general/.
- Create
queries/<topic>/ if it does not exist.
-
Write the query file:
- Filename:
<YYYY-MM-DD>-<Short Descriptive Title>.md
- Content structure:
---
date: YYYY-MM-DD
topics: ["<primary-topic>", "<secondary>"]
layers: ["L1", "L2", ...]
sources:
- "[[Page1]]"
- "[[Page2]]"
- "Clippings/_processed/<Name>.md"
---
# <Refined Question — restated with precise language>
<Full synthesized answer, with citations and any external annotations>
## Sources
- [[Page1]]
- [[Page2]]
- ...
-
Refine the question:
- The H1 heading must not be a verbatim copy of the user’s casual prompt.
- Rephrase it into a precise, self-contained question that captures intent,
scope, and any implicit assumptions. Example:
- User: "what about grpo vs ppo?"
- Refined: "What are the key algorithmic differences between GRPO and PPO in
reinforcement learning for large language models, and what advantages does
GRPO claim over PPO?"
Phase 7: No Wiki Mutation
To prevent context contamination and model hallucination:
- Do not create any new wiki pages (including concept pages, synthesis pages,
or topic pages) as a direct result of a query.
- Do not update
index.md or log.md with query records or query-derived
summaries.
- The only permitted artifact is the read-only query record under
queries/
(Phase 6).
Rationale: Query answers are ephemeral, user-managed digests. Ingesting them
back into the wiki graph risks polluting the knowledge base with unverified
synthesis and creating feedback loops where future queries cite prior LLM
answers instead of primary sources.
Phase 8: Deliver the Answer
Present the synthesized answer to the user. Mention the archived query record
(e.g., "Saved to queries/reinforcement-learning/2026-04-22-grpo-vs-ppo.md") so
they know it is preserved for future reference.
Do not mention or create any new wiki pages; the query record under
queries/ is the only persisted artifact.
Quality Standards
- Grounded: Every claim traceable to a source via
[[...]] or labeled as external.
- Layer-aware: Do not read full clippings for questions answerable from summary
pages. Do not hallucinate details when raw evidence is needed — go fetch it.
- Complete: Read all relevant pages at each activated layer before answering;
do not stop at the first match.
- Concise: Prefer synthesis over quoting large blocks of text.
- Linked: The answer itself should be dense with wikilinks so the user can explore
deeper in Obsidian.
- Persistent: Query records are archived under
queries/ for user reference, but
are never fed back into the wiki graph, index.md, log.md, or used as evidence
in subsequent retrievals.
- Transparent: Web-sourced external augmentation is flagged with
[External: <URL>]. Contradictions are always surfaced.
Directory Conventions
obsidian-paper-curator/
├── index.md # Layer 1 entry point: read first
├── papers/<topic>/ # Layer 2: processed paper summaries
├── concepts/ # Layer 2: shared concept + synthesis pages
├── queries/<topic>/ # Archived Q&A pairs (read-only; excluded from all
│ retrieval and indexing to prevent contamination)
├── Clippings/ # Layer 3: raw, unprocessed sources (read-only)
├── Clippings/_processed/ # Layer 3: archived raw sources (read-only)
└── log.md # Query audit trail
Treat Clippings/ and Clippings/_processed/ as read-only. Never modify or delete
clipping files during a query.
