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dsh-hypercompact

Deterministic, zero-LLM byte-budget context compaction engine for DeepSeek Harness with byte-exact recall tools.

VisionUI & ProductivityTerminal & TUIDeveloper ToolsSecurity & PolicySkills & Workflows
2GitHub Stars0ForksUpdated2026-10-05

Install

$ dsh plugin --profile web add dsh-hypercompact

Plugin Overview & Capabilities

AI-assisted organization based on the public repository snapshot. The content must be grounded in source evidence and does not replace compatibility or security verification.

source-grounded
dsh-hypercompact is a deterministic context compaction engine for DeepSeek Harness designed to prevent oversized request bodies and upload timeouts in long agent sessions. Instead of making expensive LLM calls to summarize transcripts, it calculates request size in bytes and performs local, millisecond-level compaction while keeping human messages verbatim and collapsing older tool outputs. It includes recall tools and commands that allow agents and users to restore full, byte-exact outputs from the append-only log on demand.

Key Capabilities

  • Byte-budget and token-ratio automatic context compaction without LLM round-trips
  • Verbatim retention and pinning of human constraints and prompt instructions
  • Single-line compression and grouping for historical tool calls and outputs
  • In-place housekeeping and image offloading to defer full compaction cache misses
  • Byte-exact recall and log searching tools (`recall`, `recall_search`) and user commands (`/recall`, `/hypercompact`)
  • Intra-turn compaction for long autonomous turns exceeding size budgets
  • Automatic recovery and single-retry on context overflow, HTTP 413, or body timeout errors

Useful For

  • Preventing upload timeouts on slow, rate-limited, or proxied network connections during extended DSH sessions
  • Compressing image-heavy and tool-output-heavy agent workflows without losing user instructions
  • Enabling agents to inspect and pull original uncompressed tool logs on demand via exact recall
  • Managing long multi-turn software development and autonomous agent sessions within strict byte limits

Who It Fits

  • DeepSeek Harness users working on long-running coding or multi-step agent sessions
  • Developers operating DSH through proxies, CDNs, or bandwidth-constrained network uplinks
  • Engineers requiring verifiable, reproducible context preservation without loss of user constraints

Documented Limitations

  • Requires DeepSeek Harness versions between 0.1.5-rc.2 and <0.3.0
  • Extractive compaction drops assistant reasoning tokens, which are not carried unless recalled
  • Must be enabled via a preset (such as the Hypercompact preset) at session initiation; existing active sessions cannot switch compaction engines mid-conversation
  • Images attached directly to user messages are not offloaded until their corresponding turn is compacted

DSH Compatibility

Version-specific runtime evidence collected by DSH Plugin. A missing result means we have not tested that combination yet.

Not tested yetNo runtime compatibility tests have been published yet.

Security Signals

Objective signals discovered from package metadata and source inspection. These are not a guarantee that a plugin is safe.

Dependency Counts

package.json declares 0 runtime, 0 development, 0 peer, and 0 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

info
License Declared

GitHub reports the repository license as MIT.

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Package Manifest Available

A root package.json was captured and can be inspected by the registry.

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Source Available

Public GitHub source metadata is available for this registry snapshot.

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Source & Registry Notes

Public provenance, Registry classification, and the latest source check for this entry, kept separate from runtime verification.

Source repository
mrbeandev/dsh-hypercompact
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
fc09a57 · 2026-10-20

This project is independently indexed from public source information. DSH Plugin is not affiliated with DeepSeek or the plugin author. Always check the author repository before installation.

Repository Activity

GitHub stars
2GitHub stars
Forks
0
Open issues
0
Last commit
2026-10-05
Last release
No release detected
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