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Context Lens — DSH Plugin for DeepSeek Harness
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dsh-context-lens

Context Lens

Request Context Profiler for DeepSeek Harness — see what changed between model requests, and how cache reuse changed with it.

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:gordonlu/dsh-context-lens#c842b84be91ad01cd3dbc8fe80f1d66f96b335a6
READMECompatibilityVersions
dsh-context-lens dashboard

Compatibility and provenance

Context Lens is published as dsh-context-lens and currently resolves to version 0.3.1. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
web
Release source
github
Registry updated
9/20/2026

Versions

0.3.1stable
9/14/2026
0.3.0stable
9/14/2026
0.2.2stable
8/14/2026
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0.2.1stable
8/14/2026

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0.3.1
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Surface
web
License
MIT
Source
github
GitHub
★ 0
Weekly downloads
432
Last push
9/14/2026
View source ↗Project homepage ↗
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README

dsh-context-lens

dsh-context-lens

Request Context Profiler for DeepSeek Harness — see what changed between model requests, and how cache reuse changed with it.

What it is

dsh-context-lens is a DeepSeek Harness plugin (server unit + client view) that answers one question continuously: "what did the harness send the model this time, and what changed since the last request?" It is a pure observer — it reads the session log, adds nothing to it, and never touches a model call.

dsh-context-lens dashboard

Quick start

dsh plugin --profile web add dsh-context-lens

Open any conversation, switch to the Request Context tab, and watch every model request get one line: what changed vs the previous request, and how cache reuse moved with it.

For every real LLM request it records one compact card:

  • Request identity — turn:step, provider, model, context window, status (completed / failed / aborted).
  • The committed request context — canonical fingerprints of the system prompt, the tool set (each tool's schema hash + estimated tokens), the request config, and the tool declaration order. Only state actually committed to a real model request is compared; the harness's mutable state is never observed.
  • Cache reuse readout — computed strictly from the provider's disjoint usage buckets (uncached input + cache reads + cache writes = billed input). Missing fields stay absent (rendered -), never zero.
  • Diff vs the previous request — model, provider, config, system prompt, tool set (+added/−removed/~modified), tool order, estimated surface delta, and the cache-reuse boundary in percentage points.
  • Drop alarm — when reuse dropped across the threshold, a ranked list of coincident changes (correlation, never causation) with an explicit disclaimer.

The view is change-first (a conversation.view slot, zh/en). Opening it answers "is anything wrong, and where?" in one glance:

  • a session status strip — ✓ cache stable / ✓ structure stable / analyzed count, flipping to ⚠ alarm counts on anomalies;
  • the recent-requests list, newest first (up to 100 retained), one line per request — a session-global ordinal, a change tag (Stable / Cache drop / Tools changed / System changed / +X tok), the cache readout, and a "hide unchanged requests" filter on by default;
  • the inspector — cache reuse with its delta, new uncached input, estimated context surface, a line-by-line comparison vs the previous request (system / tools / tool order / config / model / provider), and a green conclusion when nothing is cache-impacting;
  • raw usage buckets, header hashes, and the full tool list behind a "technical details" fold.

Accuracy boundaries

Everything on the left is genuinely observable; nothing on the right is ever claimed.

Can determineCannot determine (and never claims)
System prompt, tool set, tool schemas, declaration order, request config — as committed to the requestThe provider's internal cache key construction
Model and provider of each requestThe exact token at which prefix reuse breaks (KV-causality)
Provider-reported usage buckets (uncached input / cache reads / cache writes / output / reasoning)Which single change caused a drop — only correlation
Reuse ratio and its delta between consecutive requestsCache state of sessions/requests that left the 100-entry window
A heuristic surface estimate (chars/4 + per-block + per-role overhead)Anything about the harness's in-memory state

Architecture

Server — one pure, replayable projection (contextLens) folds the session log: request/header events (epoch-logged, committed only on change) define the snapshot in force at each step/start; a header landing inside the step replaces it (that is the header the provider actually saw). step/end marks the span closed; finalization happens at turn/end for the last step, at the next step/start for intermediate steps, and crash-orphaned logs close as failed. Retries do not mint new records (mainline retries inside the same step; the fold also splits cleanly if a future mainline opens a fresh turn). Uninteresting events return the same state reference — the registry's zero-work Object.is gate.

Replay consistency is a tested invariant: folding the log incrementally (live) and folding the same log from init (replay) produce identical state and projection.

Client — registers the context-lens entry (order 30) in the conversation.view slot, reads the projection through the framework's useProjection('contextLens') seat, and ships its own zh/en locale namespace. Selection is component-local. No heavy UI dependencies; CSS Modules compiled with lightningcss and injected as one idempotent <style> tag.

Zero overhead — no new session events, no model tools, no prompt injection, no KV simulation. A no-op companion plugin (context-lens-invariant) exists solely to reserve the package name under the harness's invariants service.

Install & build

The plugin is an npm package with a single runtime dependency (zod); all @deepseek-ai/* references are type-only. Install it into a harness profile:

dsh plugin --profile web add dsh-context-lens

Developing from source: the harness packages install from the registry (since 0.1.5 the whole @deepseek-ai/* set is published, so the old vendor-stubs/ type-only snapshots are gone). autoInstallPeers is on and zod@^4 matches the framework contract. This plugin tracks the 0.1.5 harness contract: projection units declare stateSchema + wire, the system prompt is tracked from system/message history nodes, and CLIENT_EXTERNALS mirrors the shell's new PLATFORM_MODULES. See IMPLEMENTATION_NOTES.md → "0.1.5 harness contract".

pnpm install
pnpm typecheck   # tsc --noEmit
pnpm test        # vitest — 68 tests: fingerprint, cache math, diffing, projection lifecycle, step/end, replay consistency, formatting, determinism
pnpm build       # tsc declarations → lib/types, tsdown → lib/index.js + lib/invariant.js + lib/client.js (browser, closure-factory ABI)

The browser bundle replicates the harness client-bundle ABI: window.__ModuleLoader__.load({ id: "dsh-context-lens", factory: (require) => … }), resolving react / react-dom / platform module-table entries through the loader-injected require and inlining everything else.

Real-runtime smoke scripts live in smoke/ (see smoke/README.md): a server-side smoke over the real harness packages, a client-loader ABI smoke, and a full GUI E2E against a second web instance with a mock LLM.

Layout

src/                 server: types, fingerprint, cache, diff, projection, index; companion invariant
src/client/          the conversation view + locales + CSS Modules
tests/               vitest specs incl. the replay-consistency suite
smoke/               real-runtime smokes: server, client ABI, GUI E2E
cordis.patch.yml     dsh bundle patch metadata

Roadmap

  • Retained-window cursor to inspect older requests than 100.
  • Correlation drill-down: group drops by (model, provider, tool-set hash) across the window.
  • Distinguish session-level counters from the retained window in the status strip (a drop at #127 must not read as "recent 100 are clean").

License

MIT