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dsh-llm-verifier-pro

LLM-as-a-Verifier fine-grained reward tools, Probabilistic Pivot Tournament, and Best-of-N mode for DeepSeek Harness.

VisionUI & ProductivityDeveloper ToolsSecurity & Policy
0GitHub Stars0ForksUpdated2026-09-29

Install

$ dsh plugin --profile web add github:jmche/dsh-llm-verifier-pro

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-llm-verifier-pro provides an LLM-as-a-Verifier quality gate for DeepSeek Harness. It implements fine-grained logprob reward scoring (arXiv:2607.05391), Bradley–Terry aggregation, and an O(N·k) Probabilistic Pivot Tournament. The plugin exposes three agent tools (`verify_compare`, `verify_select`, `verify_track`), a programmatically accessible `ctx.verifier` service, and an optional Best-of-N conversation mode that samples multiple responses on text-generation turns and replays only the winning candidate.

Key Capabilities

  • verify_compare tool for directed pairwise comparisons with fine-grained logprob rewards
  • verify_select tool using Probabilistic Pivot Tournament (PPT) for efficient O(N·k) best-of-N candidate selection
  • verify_track tool for offline multi-checkpoint trajectory progress tracking
  • Best-of-N (Bo-N) turn replay mode with parallel or serial candidate generation
  • Model mix support allowing diverse candidate generation across different providers and models
  • Support for TypeSafe Jev System One selector as an alternative pairwise scoring engine
  • Web settings panel integration for dynamic Cordis patch configuration

Useful For

  • Filtering and selecting the highest-quality assistant answers before returning them to users
  • Self-verification and quality grading of multi-step agent reasoning chains
  • Comparing and ranking alternative code or text candidate generations
  • Tracking task progress curves across multi-step execution checkpoints

Who It Fits

  • DeepSeek Harness users seeking test-time compute scaling and candidate verification
  • Agent developers building automated self-checking and reasoning workflows
  • Power users desiring Best-of-N answer sampling across single or heterogeneous models

Documented Limitations

  • Requires LLM endpoints supporting token-level logprobs or a compatible Jev System One endpoint
  • Does not support multimodal image or video inputs
  • Best-of-N mode only scores final text answers and deliberately skips tool-calling action turns
  • Progress tracking uses an offline single-call model rather than per-prefix online tracking

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, 10 development, 6 peer, and 0 optional dependencies.

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Dsh Bundle Declared

package.json declares DSH bundle metadata.

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License Declared

GitHub reports the repository license as NOASSERTION.

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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
jmche/dsh-llm-verifier-pro
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
9ae95d7 · 2026-09-30

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
0GitHub stars
Forks
0
Open issues
0
Last commit
2026-09-29
Last release
No release detected
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