Scan the current working session and the active task's artifacts for reusable, generalizable lessons (what was tried, what failed and why, what surprised us, what the next task should do differently) and propose anchored entries to append to the task's LEARNINGS.md, the produce-side counterpart to the ADR-0017 consume path that task-init already reads. Append-only and read-only on existing entries; de-duplicates against what is already captured; keeps durable lessons and drops one-off task trivia. Use on demand mid-task after a hard-won fix or a surprising failure, or at closure to sweep a long session before the context is lost. Do not use to rewrite or prune existing learnings (never edit prior entries), to capture a single in-flight observation (use capture-observation), to close a slice or the task (use slice-closure or task-close), or when nothing durable was learned (return a NOOP rather than manufacturing a lesson).
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryGeneralStars0
About this skill
Scan the current working session and the active task's artifacts for reusable, generalizable lessons (what was tried, what failed and why, what surprised us, what the next task should do differently) and propose anchored entries to append to the task's LEARNINGS.md, the produce-side counterpart to the ADR-0017 consume path that task-init already reads. Append-only and read-only on existing entries; de-duplicates against what is already captured; keeps durable lessons and drops one-off task trivia. Use on demand mid-task after a hard-won fix or a surprising failure, or at closure to sweep a long session before the context is lost. Do not use to rewrite or prune existing learnings (never edit prior entries), to capture a single in-flight observation (use capture-observation), to close a slice or the task (use slice-closure or task-close), or when nothing durable was learned (return a NOOP rather than manufacturing a lesson).
Quick start
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Scan the current working session and the active task's artifacts for reusable, generalizable lessons (what was tried, what failed and why, what surprised us, what the next task should do differently) and propose anchored entries to append to the task's LEARNINGS.md, the produce-side counterpart to the ADR-0017 consume path that task-init already reads. Append-only and read-only on existing entries; de-duplicates against what is already captured; keeps durable lessons and drops one-off task trivia. Use on demand mid-task after a hard-won fix or a surprising failure, or at closure to sweep a long session before the context is lost. Do not use to rewrite or prune existing learnings (never edit prior entries), to capture a single in-flight observation (use capture-observation), to close a slice or the task (use slice-closure or task-close), or when nothing durable was learned (return a NO_OP rather than manufacturing a lesson).
About this listing
Category
General
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.