AI deep-reading assistant for DeepSeek Harness and dsh-TUI: extract traceable claims, evidence, confidence levels, knowledge maps, and review questions from articles, books, PDFs, files, URLs, or pasted text.
The plugin will be installed here. Keep web if you are unsure.
npx -y @deepseek-ai/dsh plugin --profile web add dsh-deepread@1.0.1
Compatibility and provenance
Deepread is published as dsh-deepread and currently resolves to version 1.0.1. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.
Portable Agent Skill for Codex, Claude Code, and other Agent Skills-compatible tools. Zero runtime dependencies; the agent follows the evidence-first reading workflow with its own file and web tools.
Host plugin package for DeepSeek Harness Web/headless and dsh-TUI, with a deepread tool, PDF extraction, optional persistence/jobs/Web route, batch comparison, cost preview, and HTML/XMind-compatible export. Its browser client is an optional Web-only entry.
Why it is different
A typical summary
DeepRead
Compresses the topic
Extracts complete claims and the reasoning behind them
Blends source facts with model inference
Labels author intent, source facts, reasoned inference, and unverified content
Makes conclusions hard to check
Pairs important claims with evidence and page/paragraph locations
Stops at an answer
Adds knowledge maps, conflicts, limitations, and active-recall questions
If the source does not support a claim, DeepRead says “source does not provide evidence” instead of filling the gap.
Reconstructed the engineering chain from visibility to input, output, and retrieval-path compression; separated recommendations from project-authored benchmarks.
quick key takeaways · deep in-depth reading · map knowledge map · feynman Feynman technique (11-step loop + spaced repetition) · book whole-book reading (see the comparison below)
🗺️ Knowledge-map mode
Core question / core conclusion / ten content categories (conclusion, sub-claim, mechanism, fact, data, case, hidden premise, objection, limitation, actionable advice) / every claim paired with evidence (unverifiable claims marked "no evidence provided in the original text") / key data table (value & unit, time range, sample, baseline, source, location) / eight relation labels (supports, refutes, causes, explains, depends on, exemplifies, contrasts, limits) / four confidence levels (author intent, original facts & data, reasonable inference, unverifiable) / Mermaid mindmap / XMind outline / 5 active-recall questions
📥 Three inputs
WeChat article URLs (mp.weixin.qq.com stable links) · files (.txt/.md/.html/.pdf, PDF via a built-in pure-JS extractor with Chinese ToUnicode mapping, page markers, and object-stream/xref-stream support) · pasted text
📤 Optional export
Displayed in-session by default; export accepts md / mm (FreeMind, importable by XMind) / html (editor-style web report with light/dark theme) / all, written to deepread-output/ in the workspace
🎨 Browser UI
deepread tool result card (four-color confidence legend, collapsible sections) + a 📖 shortcut button next to the input area that opens a card-style reading panel (link/path/text + mode/export selection + reading focus + one-click start)
🔀 Batch compare
Pass 2-10 documents via batch (url/path/text each) to get per-document summaries plus a cross-document report: comparison matrix, conflicts, complementarity, and synthesis
📍 Citations
Reports carry page/paragraph provenance: arguments, quotes, and a dedicated citation table locate claims back to 【第N页】 markers in the source
🧮 Cost preview
estimate: true previews token spend, model-call count, and expected time per mode without calling the model (CJK≈0.6 tok/char heuristic; rate/latency defaults are picked per model family and can be overridden explicitly)
Long articles are auto-split, section-by-section + summary
map
Research, fact-checking before citing
Core question & conclusion, ten content categories, claim-evidence pairing, key data table (five elements), eight relations, four confidence levels, Mermaid mindmap, XMind outline, active-recall questions
Structured pipeline, multiple calls
feynman
Truly learning it and teaching it to others
11-step loop: TOC → questions → per-chapter → claims/data/evidence → chapter mindmap → explain with the book closed → self-check gaps → correct against the source → merged mindmap → explain again → spaced review on days 1/3/7/14/30
Longest output, most calls
book
Whole books / very long texts
Table of contents, chapter flow, a full-book summary assembled from per-part deep reads
Processed part by part
One-line picker: in a hurry, quick; read one article thoroughly, deep; cite and fact-check, map; learn and remember, feynman; a whole book, book.
Installation
DeepRead 1.0.1 requires Node.js 22.19 or 24 and higher (^22.19 || >=24). The same npm package exposes the TypeScript Host entry at lib/types/index.js, the dsh-TUI Community Consensus v0.15 manifest at dsh-plugin.json, and an optional DeepSeek Harness Web client at lib/client.js.
Host compatibility
Host
Node deepread tool
Web client
Packaged skill
Degraded behavior
DeepSeek Harness Web 0.1.2-rc.1
Supported
Web UI loaded
Available
None
DeepSeek Harness headless 0.1.0-rc.7
Supported
Web client not loaded
Available
No budget HTTP route
dsh-TUI 0.8.1 minimum / Community Consensus v0.15
Supported
Web client not loaded
Available
No Web route or browser UI
Custom composition without storageDomain
Supported
Depends on Web services
Available
URL cache and Host calibration use in-process state
Before replacing 0.5.4, read the Upgrade and rollback guide, including the browser-origin and DSH_HOME retention conditions. The Release notes describe the compatibility and entry-point changes.
DeepSeek Harness (tool + Web UI, full functionality)
Requires pnpm on the machine (dsh plugin runs pnpm underneath to install plugins).
After 1.0.1 is published, the unpinned command installs the stable npm release. Pin 1.0.1 when an exact deployment version is required.
# Stable npm release (after 1.0.1 is published)
dsh plugin --profile web add dsh-deepread
# Exact npm version (after 1.0.1 is published)
dsh plugin --profile web add dsh-deepread@1.0.1
# Exact GitHub tag (after v1.0.1 is created)
dsh plugin --profile web add "github:xiehuan123/dsh-deepread#v1.0.1"
To remove DeepRead from the Web profile:
dsh plugin --profile web remove dsh-deepread
pnpm workspace-root compatibility
Some DSH releases create each profile as a pnpm workspace but forward add and remove without marking the workspace root explicitly. With affected pnpm versions, the command stops before any DeepRead code runs and reports ERR_PNPM_ADDING_TO_ROOT. Retry only that failed operation with -w (the pnpm shorthand for --workspace-root):
# Install after ERR_PNPM_ADDING_TO_ROOT
dsh plugin --profile web add -w dsh-deepread
# Remove after the same workspace-root error
dsh plugin --profile web remove -w dsh-deepread
This is a profile package-manager compatibility issue and can affect any DSH plugin installed into that profile. Do not delete pnpm caches or edit node_modules by hand; let dsh plugin update the profile manifest and bundle list.
Restart dsh web for it to take effect. A 📖 shortcut button appears next to the input area; click it to open the card-style reading panel. You can also just say: "Read this article in knowledge-map mode: ".
Tip: fetching WeChat article URLs needs an HTTP provider. If you see "web fetch service unavailable" after install, mount @deepseek-ai/dsh-web-fetch-http in the profile's cordis.patch.yml and give it a browser User-Agent (WeChat serves an anti-bot verification page).
dsh-TUI (Host tool + skill)
dsh-TUI 0.8.1 or newer can install dsh-deepread@1.0.1 through the host's plugin installer. The installer reads the packaged dsh-plugin.json v0.15 manifest and loads lib/types/index.js; it does not load lib/client.js.
Codex / Claude Code (skill form, zero dependencies)
Install (pick one):
claude plugin install xiehuan123/dsh-deepread # terminal command (Codex compatible)
/plugin install xiehuan123/dsh-deepread # or the in-session slash command
npx skills@latest add xiehuan123/dsh-deepread # or skills.sh
Usage (Codex / Claude Code):
Trigger: say something containing "deep-read / analyze / knowledge map / Feynman", e.g.
Deep-read docs/architecture.md
Analyze this article in knowledge-map mode: <paste text>
Read this book with the Feynman technique and give me a review plan
Quickly summarize this WeChat article: https://mp.weixin.qq.com/s/xxxx
Mode: the agent picks a mode automatically (default deep); it asks when unsure.
Input: file path / web link (WeChat articles are fetched directly; for anti-bot sites like Zhihu/Juejin, paste the text) / pasted text. PDFs work too (the agent extracts text per SKILL.md; scan-only PDFs should be OCR'd first).
Output: a Markdown report in the conversation by default; say "export html / mindmap / md" and it writes to deepread-output/ in the workspace (.md report, .mm FreeMind mindmap [importable by XMind], .html web report).
Knowledge-map mode: output carries four confidence levels (author intent / original facts & data / reasonable inference / unverifiable), and every claim is paired with evidence — the original text lacking evidence is explicitly marked "no evidence provided in the original text".
Feynman mode: the full 11 steps (TOC → questions → per-chapter → claims/data/evidence → chapter mindmap → explain with the book closed → self-check gaps → correct against the source → merged mindmap → explain again → spaced review on days 1/3/7/14/30).
Note: the Codex/Claude skill is the "methodology" form — the agent performs the analysis with its own tools; the DSH deepread is the "tool" form — the plugin runs the pipeline by calling the model directly. Output formats are identical and interchangeable (an exported .md/.html keeps working when handed to an agent on either host).
Examples
Please deep-read this link: https://mp.weixin.qq.com/s/xxxx
Read book.pdf in knowledge-map mode and export html
Quickly summarize this article: <paste text>
Parameters
Parameter
Type
Description
url
string
Stable WeChat article link (mp.weixin.qq.com only; for anti-bot sites, paste the text)
The @deepseek-ai/* host packages (cordis / dsh-tools / schemastery / dsh-storage-domain) plus zod and react
are provided by the host profile and declared in peerDependencies (* means "follow the host version");
dsh.client.inject declares the client-side dependency edges (dsh-api-session-controller provides sessions,
dsh-client-ui-conversation provides conversation).
Full-text cache
Fetched article full texts are persisted following the official storageDomain convention: the
deepread_url_cache domain (version 1, zod-schema validated, records hold url/text/fetchedAt),
stored under $DSH_HOME/storages/ and surviving process restarts. Re-reading the same article in a
different mode (deep→map/feynman/book) reuses the cache without network access; when a fetch fails the
cache is used as a fallback and the report says so. Default TTL is 7 days with a cap of 200 entries
(expired entries are lazily removed on write). A composition that omits storageDomain degrades to
an in-process cache. webServer is optional: Web-capable profiles register the budget route, while
the stock headless profile activates the Host tool without that route or the browser client.
Plugin configuration (Config)
timeoutMs (default 900000), chunkChars (default 6000), maxParts (default 20),
maxInputChars (default 400000), cacheEnabled (default true), cacheTtlHours (default 168,
0 disables caching) can all be overridden in the cordis row, for example:
Before maintaining the host integration, read the DeepSeek Harness plugin integration reference. It records profile loading, the Node/browser entry points, slot lifecycle, theme rules, and the diagnostic order.
npm run typecheck:host # strict Host typecheck
npm run typecheck:browser # strict browser typecheck
npm run build # build lib/types and lib/client.js
npm test # full repository contract suite
npm pack --dry-run --json # inspect the publishable file list and public entries
If traceable AI reading is useful to you, star the repository to make it easier for the next reader to find and to follow future releases.
License
MIT
The Web panel keeps a local history of recent reads with one-click re-read (localStorage, no server round-trip)
⏳ Progress transparency
Long reads / big PDFs / batches become official background jobs: the label states segment count and budget; the progress stream pushes 「精读第 3/20 段…」 line by line; job_output polls progress and the final report, job_kill cancels
🔍 Parse progress
Full PDF extraction moves inside the background job and streams per page — 「解析 PDF 中… 42%（10/24 页）」 — after a fast sampling preflight decides length (no more silent wait before the background job appears); batches stream per document — 「解析第 2/5 篇… / 精读第 2/5 篇… / 完成第 2/5 篇」 plus 「跨篇对比汇总中…」
🧮 Panel budget
The Web panel shows per-mode token + time hints above the mode chips (e.g. 深度精读 (≈38k token · ≈8分钟)), instantly for pasted text; calibrated by real model speed; links/file paths are fetched and estimated by the Host through a same-origin API (POST /api/deepread/budget) and the panel's 🔍 budget-preflight button shows a one-line result (≈N chars · ≈X token · ≈Y min) right inside the panel — no chat round-trip, no table
⚡ Fast preflight
estimate mode samples the first 2 PDF pages and extrapolates by page count, so big PDF budgets come back in milliseconds
🎯 Self-calibration
Real token/s measured from every model call feeds a rolling average persisted in storage — estimates converge to your actual provider speed; cold-start defaults are per model family (DeepSeek/Kimi/Qwen ≈100-110 tok/s, Claude ≈70, GPT ≈90)
