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reflect-on-agent-sessionslisted

Reflect over coding agent sessions using autosearch, find recurring workflow problems, and produce a markdown report with reproducible query evidence and explicit reasoning for each issue.
mistakenot/auto-stack · ★ 0 · AI & Automation · score 56
Install: claude install-skill mistakenot/auto-stack
# Reflect On Agent Sessions Use this skill when you need to find process or engineering problems in past coding sessions and write a report. ## Output Contract - Output is a single markdown file. - Keep the report machine- and human-readable. - Report filename must include the executing agent name. - Every issue must include: - issue frequency fields (`times seen`, `first seen`, `most recent seen`), - search evidence bullets (exact query commands used), - thought process bullets (how you interpreted the evidence), - representative message/session evidence. - Bullets should be one sentence each. ## Report Filename Rule Use this filename format: ```text <report-topic>-<agent-name>-<yyyy-mm-dd>.md ``` Examples: - `workflow-issues-codex-2026-03-22.md` - `workflow-issues-claude-opus-4-6-2026-03-22.md` If the runtime exposes a more specific agent identifier, include it in `agent-name`. If not, use a stable fallback such as `codex`. ## Standard Workflow 1. Define the analysis window and workspace. 2. Refresh index with `autosearch index`. 3. Run broad discovery searches to map failure patterns. 4. Run focused searches per issue family to quantify impact. 5. Validate representative incidents with `autosearch message describe`. 6. Expand context around user-question signals before drawing conclusions. 7. Write a markdown report with issue severity, evidence, reasoning, and remediation. ## Required Issue Frequency Fields For each issue, always report: - `times see