activity-listing
The activity-listing skill enumerates discrete implementation activities required to execute an experiment design by spawning a customized subagent with full MCP tool access. Use this skill when you need to break down a complex experiment into actionable implementation steps and require a dedicated agent to comprehensively identify all required activities.
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine /tmp/activity-listing && cp -r /tmp/activity-listing/skills/activity-listing ~/.claude/skills/activity-listingSKILL.md
# SOP: Activity Listing Enumerate all discrete implementation activities required to execute an experiment design. Subagent — spawned via subagent-spawning/spawn-agent skill. <!-- BEGIN available-tables (generated) --> ## Available SOPs Optional, no fixed order; the final leaf is always a sop. | SOP | When to use | | --- | --- | | spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. | <!-- END available-tables (generated) -->
Experiment-specific - summarize the DARE executor's research design into a clean research_result report, forced to write back into the spec file produced by formated-specs.
Experiment-specific - replaces writing-specs, emits DARE's 4-layer call plan as a clean research_graph schema. Last step forces load formated-result.
loss-1 judge - read a sample's full dialogue and decide whether the user simulator semantically enacted its Policy Card. check-blind.
loss-2 judge - pairwise quality comparison across the n rungs within one topic; decide monotonicity and endpoint separation. check-blind, D1-D5 only.
Strategy: Inference to the best explanation in the face of anomalies
Remove components one by one, observe system changes to reveal hidden
Map system architecture to ablatable units for ablation studies
Design ablation studies to isolate component contributions in ML systems