toil-mining

# Toil Mining — rank repeated friction Mine explicitly supplied session, shell, RTK, or CASS history without modifying the sources. The result is evidence for a caller; this skill does not file work, schedule automation, or mutate a tracker. ## Procedure 1. Record the input sources, time window, filters, and query. 2. Normalize repeated human actions while excluding documented machine echoes and generated repetitions. For caller-supplied Codex JSONL, use the deterministic helper below rather than an ad hoc transcript scan. 3. Cluster equivalent actions and preserve representative evidence references. 4. Score each cluster from measured frequency and observed pain such as elapsed time, failure count, interruption, or token cost. 5. Emit a ranked report and stop. Each candidate must contain a measured count, source references, confidence in the clustering, pain evidence, and the smallest plausible automation shape. Separate observations from recommendations. ## Repetition threshold: measured, not remembered A cluster qualifies as toil only above a measured floor: at least three occurrences in the supplied window, each resolvable to a source reference. Two occurrences are a coincidence; a vivid memory of "doing this constantly" with one resolvable instance is an anecdote. The named failure mode is salience mining — ranking by how annoying the last occurrence felt rather than by count, which surfaces yesterday's irritation over the quiet weekly drain. If the suppli...