Use when organizing raw material into a coherent structure, defining the throughline of a piece, building an outline, or making strategic decisions about what to include and cut from generated content.
日本語の概要は準備中です。原文の説明を表示しています。
Use when ingesting source material for a writing project, building a knowledge map from notes and documents, identifying research gaps, or preparing a research corpus for content creation.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
The Research Intake specialist traverses, indexes, and maps source material into a structured knowledge map before any content creation begins.
Lead: AI traverses and indexes source material, builds the knowledge map, identifies gaps. Support: Human steers gap-filling priorities, validates the map, and seeds with context about what matters.
This skill handles Obsidian vault files, markdown notes, reference documents, prior research, and web URLs. It assumes arbitrary nested file and folder structures with no predetermined naming conventions or organizational schemes. The skill does not assume Zettelkasten, PARA, or any other specific note-taking methodology.
The knowledge map is a structured inventory of what the research corpus contains, what it lacks, and how its pieces connect. It is not an outline or a content plan -- those belong to downstream skills.
Establish session context -- Use AskUserQuestion to determine the source material location. Ask for the vault path, working directory, or confirmation that no vault exists. If a vault path is provided, confirm it before traversal. If no vault exists, ask the human to provide files, folders, or URLs directly.
Traverse and index all source material -- Recursively read every file in the provided path. For each file, extract: title or filename, topics covered, key claims made, sources cited, depth of coverage (deep, moderate, or surface), and any metadata present. Do not skip files based on naming or format assumptions. Read everything.
Build knowledge map -- Synthesize the indexed material into a structured knowledge map. Group topics with depth assessments. Extract key claims with their supporting sources. Identify connections between topics across different files. Catalog all existing sources. Surface gaps where coverage is thin or missing. See references/intake-process.md for the full indexing methodology and output format.
Present gaps for human steering -- Use AskUserQuestion to present identified gaps as a multi-select list. The human chooses which gaps to investigate. Do not fill gaps without explicit human selection. For each selected gap, propose 3 specific research directions plus a skip option. See references/gap-analysis.md for gap categories and the investigation process.
Fill selected gaps and offer vault capture -- Research the human-selected gaps via web search and synthesis. Present findings for validation before any storage. Offer to capture findings as structured notes in the vault path established in step 1. The knowledge map plus any gap-fill results become the input to the content-strategist or madman phase.
| Topic | Reference | Load When |
|---|---|---|
| Indexing methodology, traversal process, knowledge map format | references/intake-process.md | Traversing sources, building the knowledge map |
| Gap categories, investigation process, vault capture format | references/gap-analysis.md | Presenting gaps, filling selected gaps, capturing findings |
MUST DO:
MUST NOT DO:
Every Research Intake artifact opens with YAML frontmatter so downstream phases can trace provenance:
---
type: knowledge-map
version: N
derived-from:
- <source-file-or-url>
---
Research intake starts the outer loop, so parent is omitted. derived-from lists the indexed sources; use a folder or vault path when there are too many to list. Increment version when the map is rebuilt with new material or gap-fill results. Vault notes captured in Step 5 keep the vault's own note format.
# Knowledge Map: [Domain]
## Topics Covered
- [Topic A]: [deep / moderate / surface] -- [primary source files]
- [Topic B]: [deep / moderate / surface] -- [primary source files]
## Key Claims and Arguments
- [Claim 1] -- supported by [source/note], strength: [strong / moderate / weak]
- [Claim 2] -- supported by [source/note], strength: [strong / moderate / weak]
## Existing Sources
- [Source 1]: [what it covers], [file location]
- [Source 2]: [what it covers], [file location]
## Connections Identified
- [Topic A] relates to [Topic C] through [mechanism]
- [Claim 2] contradicts [Claim 5] on [specific point]
## Gaps Identified
1. [Gap description] -- [category: undeveloped / unsupported / missing perspective / outdated]
2. [Gap description] -- [category]
The knowledge map is the central artifact of this skill. It serves as a structured inventory rather than a content plan. The distinction matters: a knowledge map says "here is what exists, here is what is missing, here is how pieces connect." A content plan says "here is what to write and in what order." The research-intake skill produces the former. Downstream skills like the content-strategist consume the knowledge map and transform it into editorial decisions.
Gap analysis follows a four-category model: undeveloped topics (mentioned but not explored), unsupported claims (asserted without evidence), missing perspectives (one-sided coverage), and outdated material (superseded by newer information). Each category implies a different research action. Undeveloped topics need exploratory research. Unsupported claims need source verification. Missing perspectives need deliberate counter-sourcing. Outdated material needs current-state research. Categorizing gaps before investigating them prevents wasted effort on low-value research directions.
The depth assessment scale (deep, moderate, surface) provides a quick triage of coverage quality. Deep coverage means the source contains detailed evidence, multiple supporting examples, and nuanced argumentation. Moderate coverage means the topic is addressed with some evidence but lacks exhaustive treatment. Surface coverage means the topic is mentioned or referenced without substantive exploration. This three-level scale is deliberately coarse to enable fast indexing across large source collections without getting bogged down in granular scoring.
Connection mapping across source files reveals relationships that no single document contains. When two notes discuss the same concept using different terminology, the knowledge map surfaces this overlap. When one note's conclusion contradicts another's premise, the knowledge map flags the tension. These cross-file connections are among the most valuable outputs of the intake process because they represent insights that exist in the corpus but are invisible to anyone reading files in isolation.
The human steering step for gap-filling prevents wasted research effort. Not every gap is worth investigating. A gap in a peripheral topic may be irrelevant to the planned content. A gap in a core topic may be critical. Only the human can make this judgment because only the human knows the editorial intent. Presenting gaps as a structured multi-select list with categories and proposed research directions gives the human enough information to decide without requiring them to formulate the research plan themselves.
Maintained by @jeffallan, Principal Consultant at Synergetic Solutions
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概要と使いどころ
Use when organizing raw material into a coherent structure, defining the throughline of a piece, building an outline, or making strategic decisions about what to include and cut from generated content.
日本語の概要は準備中です。原文の説明を表示しています。
Use when writing prose from a structured outline, building draft content section by section, or constructing clear sentences and paragraphs from an approved blueprint.
日本語の概要は準備中です。原文の説明を表示しています。
Use when planning a multi-article content strategy from a research corpus, creating domain maps for content topology, building production plans for pillar and cluster articles, or tracking cross-article production.
日本語の概要は準備中です。原文の説明を表示しています。
Use when editing a draft, checking for AI voice patterns, reviewing prose quality, running readability analysis, auditing consistency, or validating SEO requirements on finished content.
日本語の概要は準備中です。原文の説明を表示しています。
Use when capturing research artifacts to a vault or knowledge base, formatting source citations, saving synthesized connections from a writing project, or enriching a knowledge base with produced content.
日本語の概要は準備中です。原文の説明を表示しています。
Use when brainstorming ideas, generating raw material, or starting the creative phase of a writing project. Invoke for topic exploration, idea generation, angle discovery, or producing abundant raw content before organizing.
日本語の概要は準備中です。原文の説明を表示しています。