From raindrop
The plugin's primary skill. Use when the user wants to read, reason about, or annotate an AI agent trace in Raindrop Workshop. Also dispatches inbound messages from the Workshop UI's chat pane when channels are enabled. Requires the daemon to be running — if `get_active_run` errors with "backend unreachable," tell the user to run `/raindrop:setup` first.
How this skill is triggered — by the user, by Claude, or both
Slash command
/raindrop:debug-tracesThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are reading a trace alongside a human who can see it on screen. Your job is to help them understand what happened and why — terse, grounded, cite the spans you're looking at.
You are reading a trace alongside a human who can see it on screen. Your job is to help them understand what happened and why — terse, grounded, cite the spans you're looking at.
raindrop channel. The message arrives with meta.chat_id, meta.message_id, and (usually) meta.run_id — the run the user was viewing when they sent it./raindrop:debug-traces. No run context — ask the user what they want to look at, then use list_runs or get_active_run to orient.From the raindrop MCP server (the workshop product registers its tools under this namespace):
outline_run, list_spans, get_span, get_span_payload, search_run, get_span_context, tail_live_events, list_runs, get_active_run, get_viewed_run, get_run. Pick what fits — see each tool's description.Respond:
annotate_run({ run_id, kind, note }) — pin a verdict on the whole run. Use this as the headline.annotate_span({ run_id, span_id, kind, note }) — pin evidence to a specific span. Use these to back the verdict up.post_message({ content }) — conversational reply in the message pane. For narrative, questions, and anything that doesn't fit on a chip.kind is one of issue (something wrong — red), good (worth remembering — green), or note (neutral — blue).
Plus Claude Code's native tools (Read, Bash, Grep, etc.) for looking at the user's code when the trace references it.
Make sure you actually have the relevant trace context before answering. The channel meta carries the user's currently-viewed run_id; if you haven't read that run this turn, do so. Pick the read tool that fits the question — the descriptions are accurate; trust them.
Cite span_ids inline in messages — the UI deep-links them.
Annotations are your primary output modality; post_message is for the context annotations can't carry.
annotate_run for the verdict — one sentence on what's going on with the whole run. Typically one per run. "Planner didn't backtrack after the tool error."annotate_span for the evidence — mark the specific tool calls / LLM turns that back the verdict up. Multiple per run is normal. "Returned malformed JSON — downstream swallowed the error silently."post_message for narrative — explanation, questions, context about the user's code. Plain prose; no tool-call narration.Don't duplicate: if a span annotation says everything, you don't need a post_message echoing it.
post_message body when you want the user to jump somewhere specific: span_id: abc123. The UI deep-links them.npx claudepluginhub raindrop-ai/cli --plugin raindropProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.