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Clearailhc/clearai-dsh

ClearAI is a native DSH plugin that brings the Epistemic Loop to DeepSeek Harness.

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agent-presetai-agentsdeepseek-harnessdshdsh-plugindsh-pluginsepistemic-loopscientific-discovery
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Created Sep 12, 2026Updated Oct 1, 2026

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README

ClearAI

English · 中文

Clearailhc%2Fclearai-dsh | Trendshift

Your research, grown into an ontology.

ClearAI is an ontology discovery and exploration platform, built on two core concepts:

  • Domain ontology (what you get) — your project's own vocabulary, the knowledge entries established through the loop, and their graphs. At the end of a research session you hold a continuously growing knowledge structure, retrievable next round by concept.
  • Epistemic loop (how you get it) — a disciplined seven-stage path: frame, hypothesize, plan, observe, verify, evaluate, record. Every edge is tested by evidence and independent evaluation.

Other knowledge graphs pile up edges by extraction and assertion; here every edge has to be earned through the loop.

# Install (npm package, prebuilt — no build step, no allowBuilds prompt)
dsh plugin --profile web add clearai-dsh@0.3.1
# or in the app: Plugins → Add plugin → clearai-dsh@0.3.1

Restart dsh web, then pick ClearAI in the preset picker at the top of a new session. That is the whole setup. Full install notes ↓

The epistemic loop (left) growing a domain ontology (right)

Left: the Epistemic Loop — seven stages. Its emerald fact dot is also the first node of the domain ontology on the right. Right: the ontology graph — dark is a concept, light is a value form, emerald an instance; the instance carries two contradictory assertions — the two readings are tinted amber, marking that they do not agree. The system reports the conflict; retracting or keeping is a human decision.


What you get: a domain ontology

A domain ontology that grows as you research:

  • Vocabulary — the language your project speaks: concepts, predicates, value forms, units. Conventions themselves carry no truth value; sentences written with them do.
  • Established entries — knowledge that passed the loop: each with its boundary, support level, and evidence chain. Each entry states its boundary explicitly, so it can be cited safely.
  • Ontology graph and entity graph — what your domain looks like (structure), and what you have actually verified (the state of play).
  • Conflict readings — contradictory conclusions surface automatically; the system reports them, and retracting or keeping is your decision.

How you get it: the Epistemic Loop

Most agent loops track one thing: whether the task is done. The Epistemic Loop also tracks what makes a conclusion trustworthy:

Task loop Epistemic loop
Driving question What next? What do we know, and on what grounds?
Completion The model declares it The system computes it from delivered evidence
Verdict Whoever did it, says so Separated — above a level, the doer cannot judge themselves
Failure Deleted, retried, forgotten Kept: a refuted hypothesis is a result, not noise
What accumulates A chat transcript An ontology: every edge earned through the loop
The Epistemic Loop

Inside the ring is the instrument's read-out: the L0–L4 axis, the pre-registered threshold as a dashed line, and five observations with error bars — the supported one filled, the inconclusive drawn as a dashed circle, the refuted left in place with a slash through it (nothing is deleted). The emerald dot at the opening is the one reading that crossed the threshold and settled as a fact.

At runtime, the seven stages compress into four beats — plan, execute, observe, reflect. State is derived from the session record with no second store; the tools the model holds contain no field in which it could declare a step complete.

ClearAI does not claim recursive self-improvement. It provides the epistemic substrate a self-improving system would need. See Positioning and the OpenRSI survey.


Install and use

Requirements: DSH ≥ 0.1.7-alpha.1 — that generation introduced the composition declaration line this preset rides on. Verified against the host's 0.1.7-rc.2 and 0.2.0-rc.1.

Recommended — install it in the app, with the version pinned:

In the sidebar open Plugins → Add plugin, enter clearai-dsh@0.3.1, and install. That is DSH's own plugin manager: it hands what you type to pnpm, checks that the package declares a bundle and is compatible with this host, and applies it live. (The Settings page 插件列表 / Plugins is the read-only inventory — installing happens on the sidebar's Plugins page.)

Or from a terminal — the same install:

dsh plugin --profile web add clearai-dsh@0.3.1

This installs the prebuilt package from the npm registry. Nothing is compiled on your machine, so there is no allowBuilds grant to approve — the plugin is ready the moment the command returns.

Why the version is pinned. pnpm ≥ 11 holds back newly published versions: minimumReleaseAge defaults to 1440 minutes, and because that built-in default is non-strict, a bare package name (or @latest) silently falls back to the newest version older than a day — right after a release, the previous release. DSH's plugin manager forwards your spec to pnpm unchanged and does not compare what landed against what you asked for, so this downgrade is reported as a success. Its preview card is no help either: it reads the package with pnpm view, which ignores the age policy, so it can show the newest release while pnpm installs the one before it. Two ways to be exact:

  • Pin the version, as both commands above do — pnpm then records the exception itself.

  • Or exempt the package once in the profile's pnpm-workspace.yaml; a bare name works from then on:

    minimumReleaseAgeExclude:
      - clearai-dsh

Also available — one-command installer (it resolves the current release and pins that version for you, so it is immune to the delay):

npx clearai-dsh install

Same install underneath; it resolves the DSH CLI from your PATH (or through npx), installs into the web profile, and reads the composed config back so you are not taking "success" on faith. Use this if you prefer a guided path, or --lang zh|en to force the installer's output language.

Community market (third-party): dsh-market lists whatever the curated awesome-dsh-plugin catalog carries and installs a pinned version for you; ClearAI's catalog entry is in review there. It is not part of DSH, and it is not needed to install this plugin.

Install from source (for development, not the normal path):

dsh plugin --profile web add github:Clearailhc/clearai-dsh

Git fetches source rather than build artifacts, so pnpm ≥10 will refuse to run the prepare script until you add an allowBuilds entry to the profile's pnpm-workspace.yaml. That grant means permission for this package's code to execute on your machine at install time — grant it only if you have read the source, and pin a commit. If you just want to use ClearAI, use the npm install above.

The installer's output follows your system language (--lang zh|en overrides it, doctor / seed / unseed take the same flag). Its only runtime dependency is zod; the graph stack is bundled into the client half at build time.

Restart dsh web afterwards (npx @deepseek-ai/dsh web), then create a session and switch to the ClearAI mode in the picker at the top:

  1. Open dsh web and click "New session";
  2. Click the current mode name at the top (default: Standard mode) to open the preset list;
  3. Pick ClearAI — its card reads "利用认识论循环构建可信本体。Build a trustworthy ontology through the epistemic loop.";
  4. Just ask your question. Ordinary Q&A runs as usual; once you set a goal and register hypotheses, the system enters knowledge mode by itself: known facts come to you, gaps stay visible, and conclusions earn their place.
The knowledge graph in ClearAI mode

The ontology graph in ClearAI mode — this real session grew 21 concepts and 9 predicates; the same ledger always yields the same picture. (UI shown is Chinese.)

If pnpm is not on PATH: npm install -g pnpm (do not corepack enable — it installs a version forwarder that may download a pnpm it cannot launch).

From the repository:

npm test                       # 18 suites
node tools/build-package.mjs   # assemble dist/ from source
node tools/verify-package.mjs  # rebuild on the spot, byte-compare
node docs/diagrams/build-hero.mjs   # redraw the product hero (needs google-chrome)

dist/ is generated and never committed. See DSH integration.


What it looks like

The middle column has two switchable views: Deliverables and Ontology. The right sidebar: Worldlines and External Brain.

Ontology — this view is your knowledge home. At the top, a graph band: the ontology graph (what your domain looks like) and the entity graph (what you have actually verified) toggle with one click; clicking a node or edge opens the knowledge inspector (definition / relations / assertions / evidence chain / history), and "filter by this" is an explicit action inside the detail view. Below that, the ontology shelf: established entries, each with assertion chips (click to see what the term means), boundary, and support level; contradictions surface automatically. The vocabulary maintenance block sits collapsed at the bottom — it auto-expands when a language exists before any sentence does.

The graph band: ontology graph and entity graph

The band — the ontology graph and the entity graph share one deterministic projection, so the same ledger always yields the same picture (captured from a real session: 21 concepts, 9 predicates).

Knowledge inspector: definition, relations, assertions, evidence chain

Open any node or edge: definition, relations, assertions, evidence chain, registration and revision history, all in one place. (UI shown is Chinese.)

Worldlines — when two routes genuinely disagree, they run as separate branches with their own readings; the losing one stays on record, and adoption is a human press.

Deliverables — the middle column keeps "what the plan declared" and "what actually exists on disk" apart.

External Brain — skills and memory as DSH-native entries in one merged catalogue.


Cases

  • Physical-world process experiment — sensor thermal drift: the full chain from raising terms to a conflict surfacing
  • AI for Science — convergence order of WENO reconstructions, and what "we could not resolve it" honestly means
  • Mathematics — keeping finite numerical evidence strictly separate from proof

Documentation

  • Positioning · Domain ontology design
  • Epistemic loop · Verification ontology · Loop philosophy
  • Design principles · Soul map · Glossary
  • Knowledge-native loop ledger (this round: triage / preflight / knowledge gate / graph / inspector; zh-CN)
  • Development plan (with real-run evidence from the Hengtong project)
  • Known gaps · Authority map · Release verification

Where it sits in DSH

ClearAI adds the epistemic layer on DSH's composition plane — one host package, one agent preset, one client module, with zero changes to the DSH engine. Working style is unrestricted, but nothing outside the governed path can write to the authoritative ledger (pinned by tests).

Work attribution

This project's work attribution unit is Jidian Qiyuan.

Star History

Star History Chart

License

Apache-2.0, see LICENSE.

Status

A local-first ontology discovery and exploration platform delivered as a DSH plugin. What is not yet implemented, and what has not been verified in a real browser, is written in Known gaps.