From thinking-frameworks-skills
Systematically skims documents to classify type (methodology, tool, etc.) and determine worthiness for deeper reading. Useful for paper triage, skill extraction, and reading list pruning.
How this skill is triggered — by the user, by Claude, or both
Slash command
/thinking-frameworks-skills:inspectional-readingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
The first level of Adler's "How to Read a Book" methodology, applied as a reusable skill. Answers two questions before any deeper reading happens: **What kind of document is this?** and **Is it worth reading carefully?**
The first level of Adler's "How to Read a Book" methodology, applied as a reusable skill. Answers two questions before any deeper reading happens: What kind of document is this? and Is it worth reading carefully?
The skill is invoked autonomously by an agent — it reads the document and produces structured output. It does not host a dialogue with the operator.
- [ ] Step 1: Read the metadata (title, authors, date, source, length)
- [ ] Step 2: Read the abstract / introduction completely
- [ ] Step 3: Examine table of contents or section headings
- [ ] Step 4: Skim the conclusion and any end-material at a glance
- [ ] Step 5: Classify the document type
- [ ] Step 6: Assess worthiness for the calling agent's purpose
- [ ] Step 7: Output structured findings
Time budget: 10-15 minutes for a typical paper / chapter / methodology document. If a document needs more, you've drifted into the next level of reading — stop and produce the inspectional output you have.
The calling agent passes:
source: the document to read (path or URL or text)purpose_context: a short string describing what this document is being read for. The classification and worthiness check both depend on this — reading a paper for synthesis vs reading a methodology document for skill extraction yield different worthiness criteria. Examples:
purpose=paper_extraction_for_weekly_digest — caller is paper-synthesizer's pipelinepurpose=skill_extraction_from_methodology — caller is the skill-creator agentpurpose=reading_list_triage — caller wants to rank a backlogdomain_hint: optional. The field the document is in (life sciences, ML, philosophy, etc.) — improves classification.## Inspectional Reading Output
### Metadata
- Source: {path or URL}
- Title: {title}
- Authors / origin: {names or affiliation}
- Length: {pages, sections, or word count}
- Date / version: {date}
### Document type
Primary: {methodology | framework | tool/template | theoretical | reference/catalog | hybrid}
Secondary aspects (if hybrid): {list}
### Stated purpose and audience
{1-2 sentences from the abstract / intro}
### Structural skeleton
{TOC or section headings, in order, as a bullet list}
### Worthiness assessment (for purpose={purpose_context})
- Reusable across multiple contexts: {yes|no|partial} — {one-line rationale}
- Teachable as steps or principles: {yes|no|partial} — {rationale}
- Non-obvious (provides value beyond common sense): {yes|no} — {rationale}
- Complete enough to be actionable: {yes|no|partial} — {rationale}
Recommendation: {ESCALATE to deeper reading | STOP — not worth it | PROCEED with caveats}
### One-line summary
{single sentence, ≤30 words, what this document is}
The classification drives what the calling agent does next. Use the most specific applicable label.
| Type | Characteristics | Extraction focus | Skill-worthy default |
|---|---|---|---|
| Methodology / process | Sequential steps or phases; "first do X, then Y" | Steps, sequence, inputs/outputs, decision criteria | Yes — linear workflow |
| Framework / model | Dimensions, axes, principles, matrices | Dimensions, categories, when-to-apply, interpretation | Yes — framework with decision logic |
| Tool / template | Fill-in-the-blank, templates, checklists | Template structure, what goes where, usage guidelines | Yes — template with completion docs |
| Theoretical / concept | Explains "why", research findings, principles | Core concepts, implications, application mappings | Needs synthesis to be actionable |
| Reference / catalog | Lists, encyclopedia-like, lookup-oriented | Usually skip — but extract decision-frameworks if present | Usually NOT skill-worthy |
| Hybrid | Combines multiple types | Identify boundaries; extract each part by its type | Yes — partitioned |
purpose=paper_extraction_for_weekly_digest. The caller wants to know enough to decide whether to invest deeper-reading compute. Worthiness criteria emphasize: relevance to the watchlist, novelty vs prior weeks, whether the abstract claims something specific or vague. Paper papers fall mostly into "theoretical / empirical study" — apply the next level of reading (content grasp) only when the worthiness check passes.
purpose=skill_extraction_from_methodology. The caller wants to know whether this document is worth extracting into a SKILL.md. Worthiness criteria emphasize: is the methodology actionable (can it be turned into steps a different agent could follow), is it non-obvious (does it teach something the model doesn't already know), is it complete enough (or are there gaps that would need filling). Reference/catalog documents almost always fail; methodology / framework documents almost always pass.
purpose=reading_list_triage. The caller has a backlog of N documents and wants to rank them. Output focuses on the worthiness assessment + one-line summary; classification is secondary.
(not visible at this level) rather than guessing.paper-three-pass-extraction — wraps this skill as Pass 1 plus the paper-specific Five Cs framework, then escalates to Pass 2 / Pass 3 for content grasp + deep reading.structural-analysis — the next level of reading; called by paper-three-pass-extraction Pass 2 and by skill-creator Step 2 when this skill recommends ESCALATE.synthesis-application — the completeness-and-logic check that runs in deeper reading levels after this one.skills/skill-creator/SKILL.md invokes this skill as its Step 1.npx claudepluginhub lyndonkl/claude --plugin thinking-frameworks-skillsMaps document structure using Adler's Level 2 reading methodology: classifies content type, states unity in one sentence, enumerates major parts and their relationships, and defines the problems the document solves. Use after inspectional reading.
Reads, analyzes, and summarizes academic PDF papers — extracting metadata, research questions, methodology, results, and generating structured literature notes. Supports single paper deep dives, batch literature reviews, and cross-paper comparison.
Processes research paper PDFs from local paths, URLs, or arXiv; extracts metadata, content, links; generates study materials in user's language for deep analysis.