dsh-skill-trail
Run the following command in DeepSeek Harness:
dsh plugin install Bryan-cmf/dsh-skill-trail
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install Bryan-cmf/dsh-skill-trail in the DeepSeek Harness terminal to install; source code is available at https://github.com/Bryan-cmf/dsh-skill-trail
About this plugin
In a DeepSeek Harness conversation it is often hard to tell at a glance whether a given skill was actually triggered or whether a tool call truly succeeded versus failed. dsh-skill-trail renders a compact trail beneath every assistant reply, surfacing what was triggered, what was used successfully, and where things went wrong in that turn.
The badges are not self-reported by the model. A host-side session-projection unit folds the committed session log with a pure function: each tool-call event becomes a triggered entry, and the paired result is matched by callId to settle a success or failure verdict. The trail is structurally verifiable, replayable, and strictly per-turn, so one reply never bleeds into the next and no extra isolation realm is required.
It suits anyone who wants to audit skill-invocation chains, verify tool execution outcomes, or demonstrate to colleagues exactly what a given turn did in a DSH workspace. Note that the author has since migrated further features to dsh-skill-ledger; this repository is kept as a design-history record.
Use Cases
- Verify whether a given reply actually triggered a specified skill
- Pinpoint the exact step where a tool call returned a failure
- Show a team the full execution chain of a single conversation turn
Best For
- Developers who need to audit skill-invocation chains
- Engineers troubleshooting tool execution failures
- Technical leads demonstrating DSH workspace execution details to teammates
Related Plugins
Memory layer for coding agents that indexes local session history and auto-recalls relevant context before edits, commands, and failures, with no manual search needed.
Traceable, searchable cross-session memory for AI agents that turns conversation knowledge into a typed knowledge graph and recalls relevant subgraphs instead of replaying full history, natively integrated with DeepSeek Harness.
Gives DSH AI cross-session long-term memory, to-do and skill management, plus multi-session orchestration, external AI delegation, and an infinite canvas that grows with you.
dsh-mnemon is a three-tier, pluggable, Agent-driven memory system for DeepSeek Harness, combining Runtime memory, Project Documents, and replaceable Memory Spaces with nine long-term providers.