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dsh-model-probe

Audits and corrects llm-pi-ai model capability declarations in DeepSeek Harness by directly probing provider endpoints.

VisionUI & ProductivityDeveloper ToolsSecurity & PolicySkills & Workflows
0GitHub Stars0ForksUpdated2026-09-14

Install

$ dsh plugin --profile web add dsh-model-probe

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-model-probe is a DeepSeek Harness plugin designed to verify and correct model capability declarations for llm-pi-ai providers. Instead of relying on static catalogs or manual guesses, it actively measures actual limits such as contextWindow, maxTokens bounds, reasoning effort levels, and image input capabilities using GET /models queries, constraint elicitation errors, and runtime visual test probes. It offers both a settings UI page with backup/diff confirmations and agent tools for automated scanning.

Key Capabilities

  • Measures contextWindow, maxTokens limits, reasoningEfforts, and image input capabilities directly from endpoints
  • Uses constraint elicitation to extract parameter boundaries with 0 output tokens generated
  • Synthesizes test images in-process to verify multimodal vision support
  • Provides a dedicated settings UI (模型配置实测) with scan diffs, per-provider toggles, and safe mutate-backed write operations
  • Exposes agent tools (model_probe_status, model_probe_scan, model_probe_apply) for automated inspection and updates
  • Supports openai-completions and anthropic-messages protocols

Useful For

  • Preventing HTTP 400 errors caused by configuring maxTokens beyond a provider gateway's actual maximum limit
  • Auditing newly added llm-pi-ai endpoints to ensure declared context windows and reasoning levels match reality
  • Verifying whether a newly released model gateway supports vision inputs before routing multimodal tasks

Who It Fits

  • DeepSeek Harness users configuring custom or third-party LLM gateways
  • Developers needing accurate model metadata and token boundary verification
  • AI operators debugging silent model configuration failures

Documented Limitations

  • Supports openai-completions and anthropic-messages protocols only
  • Endpoints returning unparseable error messages for illegal values fall back to unknown without writing
  • Settings UI labels are currently provided in Chinese only
  • CLI installation requires selecting the matching active DSH profile

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, 3 development, 3 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 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
xiaomao49/dsh-model-probe
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
c5bc8d9 · 2026-09-14

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
2026-09-14
Last release
2026-09-14
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