toil-mining

Featured

Mine caller-supplied usage history for repeated toil and emit ranked evidence. Triggers: "mine toil", "find repeated operational work".

AI & Automation 446 stars 41 forks Updated today Apache-2.0

Install

View on GitHub

Quality Score: 97/100

Stars 20%
88
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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. ## Constraints - Read-only over the supplied sources, because the skill gathers evidence and must never become a mutation lane. - No work creation: it never files a tracker item, schedules automation, or names an owner, because those are caller decisions the evidence informs. - Measured, not remembered: every count, cost, and error rate is read from the supplied history, so recency and salience cannot masquerade as frequency. - Observations stay separate from recommendations, so a caller can re-weigh the ranking without inheriting an unstated conclusion. ## 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 automat...

Details

Author
boshu2
Repository
boshu2/agentops
Created
10 months ago
Last Updated
today
Language
Go
License
Apache-2.0

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

mine-skills

Mine your past agent sessions (Claude Code, Codex) for recurring failures and re-explained procedures, then distill the best candidates into reusable skills that land in the central library via `agentstack x lib add`. Local and read-only until you approve a draft.

3 Updated 1 months ago
Tarekkharsa
Data & Documents Listed

transcript-mining

Efficient, bounded mining of Claude Code session transcripts (~/.claude/projects/*/​*.jsonl) for workflow audits, usage-pattern analysis, and skill distillation — JSONL anatomy, proven extraction queries (tool-use counts, duplicate reads, token aggregation, command sequences), the scan-only-named-files rule, and the content-vs-mechanics separation rule. Use when auditing workflow health, quantifying token waste, reconstructing what happened across sessions, or distilling incident knowledge from transcripts into a skill.

0 Updated 1 months ago
beomeodev
AI & Automation Listed

skill-miner

Mine agent session logs (Claude Code, Codex, OpenCode) for user corrections, recurring failures, user frustration, token-heavy sessions, and repeated manual workflows, then find and score skills that could fix them. Use when asked "what skills am I missing", "mine my session logs", "where do my agents keep failing", "find a skill for X", "which sessions burned the most tokens", or to discover existing skills from skills.sh / Floom / local pools before writing anything new. Pairs with skill-eval-loop, which proves candidates before adoption.

3 Updated yesterday
getedgehq