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dsh-llm-trace

Wire-level LLM HTTP inspector and visualizer for DeepSeek Harness sessions and provider calls.

UI & ProductivityTerminal & TUIDeveloper ToolsBrowser & WebSecurity & PolicyRemote Execution
0GitHub Stars0ForksUpdated2026-09-21

Install

$ dsh plugin --profile web add dsh-llm-trace

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-trace is a DeepSeek Harness plugin that intercepts and captures the exact raw HTTP request and response payloads sent to model providers. It provides a session-scoped LLM Trace tab in the Conversation View and a global loopback viewer page, rendering requests as size-annotated collapsible JSON trees and reconstructing streaming SSE chunks into clear reasoning, content, and tool calls.

Key Capabilities

  • Captures exact wire-level HTTP request and response bodies by wrapping globalThis.fetch without blocking streaming responses
  • Integrates a session-scoped LLM Trace tab into the Conversation View UI with automated composer toggling
  • Provides a global loopback web viewer endpoint for inspecting all process-wide model calls
  • Renders massive JSON payloads as collapsible trees with measured byte sizes and text expansion
  • Assembles streaming Server-Sent Events (SSE) deltas back into aggregated reasoning, text content, and tool calls
  • Configurable header redaction, URL pattern matching, retention counts, and journal memory limits

Useful For

  • Debugging exact provider payloads, prompt formatting, and token bloat during agent interactions
  • Inspecting background subagent or title-generator requests across the entire Harness process
  • Analyzing detailed reasoning output, raw tool calling parameters, and streaming chunk structures
  • Measuring exact byte distribution across message arrays and provider envelopes

Who It Fits

  • Developers debugging DeepSeek Harness agent workflows and model interactions
  • LLM application engineers diagnosing prompt payloads, tool schemas, and streaming latency
  • Researchers monitoring low-level model provider network exchanges

Documented Limitations

  • Does not redact sensitive credentials or secrets within request bodies (only headers are redacted)
  • Non-default mount paths require manual matching adjustments in the client script
  • Relies on wrapping global fetch; conflicts or duplicates traces if run alongside other global fetch wrappers
  • SSE response reassembly currently targets OpenAI-formatted streaming envelopes, falling back to raw view for others

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, 1 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 Apache-2.0.

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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
wpeng77/dsh-llm-trace
Registry source
GitHub · dsh-plugin topic
Registry classification
Plugin
Source checked
9fffd23 · 2026-09-24

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
2026-09-21
Last release
No release detected
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