history-analysis

name	history-analysis
description	Use to systematically analyze the full evolution history without output truncation and produce a focused summary for selection, diagnosis, or reflection.

History Analysis (Core)

Purpose (Core)

Use this skill first in selection, diagnosis, and reflection. The canonical history is a complete event-derived navigation surface, not a terminal dump to truncate. It prevents repeated failed approaches, accidental loss of durable improvements, and decisions based only on the latest candidate.

Read The Canonical Bundle (Core)

1. Read .autosaddler/history/manifest.json and verify its event boundary, entry points, limits, and explicit omissions.
2. Read summary.json for accepted lineage, candidate statuses, measured development aggregates, changed-unit summaries, and detail paths.
3. Read current_batch.json, then follow relevant case and iteration paths for the current training batch.
4. Read lessons.json for recorded good and bad patterns from prior iterations.
5. Open candidate details and diffs only when the current decision depends on them. Read each selected artifact completely within its declared limits.

Do not search arbitrary run files for development or test records beyond the aggregate fields supplied by the bundle.

Classify Prior Changes (Core)

Classify relevant changes as:

• durable improvement: a measured gain with a plausible mechanism that survives later evaluation or descendants;
• fragile improvement: a gain observed once, with weak attribution or later instability;
• regression: a change linked to previously working behavior becoming worse;
• ineffective attempt: a measured change that did not repair its target;
• rejected mutation: useful verifier or contract evidence, but never a candidate outcome;
• uncertain: insufficient, conflicting, or stochastic evidence.

Track repeated failed approaches, regression-prone units, durable changes that must be preserved, and complementary strengths across accepted candidates. Distinguish lineage health from a single score: a high-scoring branch may still carry unresolved regressions or coupled changes.

Session Focus (Core)

• Evolution: compare selectable accepted parents, durable gains, regressions, compatible units, and whether composition is attributable.
• Diagnosis: find prior attempts on the current failure pattern, proven or failed interventions, and units whose modification has broad impact.
• Reflection: determine what the current result adds beyond existing lessons and whether similar outcomes have been durable or stochastic.

Produce a focused assessment that directly supports the current session. Do not restate the entire history when a smaller evidence-backed comparison is sufficient.