From agent-session-resume
Resumes or audits prior AI coding-agent sessions across platforms (Claude Code, Codex, Cursor, etc.) by locating transcripts, reconstructing context, and extracting tasks with evidence references.
How this skill is triggered — by the user, by Claude, or both
Slash command
/agent-session-resume:agent-session-resumeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Resume or audit prior coding-agent work with continuity. Reconstruct what happened before acting, then continue from the real stopping point.
agents/openai.yamlreferences/antigravity.mdreferences/claude-code.mdreferences/codex.mdreferences/cross-platform.mdreferences/cursor.mdreferences/evidence-and-provenance.mdreferences/github-copilot.mdreferences/opencode.mdscripts/session-candidates.pyscripts/session-digest.pyscripts/session-events.pyscripts/skill-provenance.pyResume or audit prior coding-agent work with continuity. Reconstruct what happened before acting, then continue from the real stopping point.
Run a provenance self-check.
python3 skills/agent-session-resume/scripts/skill-provenance.py when available.$HOME/.claude and ${CODEX_HOME:-$HOME/.codex}.Loaded skill line of the resume report. Details: references/evidence-and-provenance.md.Identify the source. If the user names a platform, read the matching file in references/; if the ask spans platforms, read references/cross-platform.md. Otherwise inspect the workspace for session folders, exports, summaries, and artifacts. When a session title is given, prefer exact or fuzzy title matches over recency.
Locate the transcript or best substitute. Prefer full transcripts over summaries, workspace-local session data over global history, and explicit user-provided paths over discovered paths.
Read the full available session record before acting. For large transcripts, inventory files, event types, and timestamps first, then read the evidence-bearing slices until the record is accounted for. Full coverage means no relevant evidence skipped; bounded searches and slices are fine for giant records, but say so and name the file/event. Do not edit files or repeat prior work before this pass is complete.
Record loaded-skill provenance in the report: path and source/version marker, or unknown, never a guess. Details: references/evidence-and-provenance.md.
Reconstruct context. Summarize the goal, decisions, constraints, and preferences; identify completed work, changed files, commands and tests run; pin the exact stopping point. Every work-state claim carries an evidence ref (src/file.ts:L20-L35, transcript lines, command output, or explicit "not checked yet"). Prior resume reports, summaries, and handoffs are claims, not primary evidence: re-verify against transcripts, files, git state, or command output, or label them unverified. Preserve explicit user deferrals ("skip", "park", "not now", "hold") with evidence, scope, and reopen condition.
Extract tasks. Capture explicit TODOs, plans, and open questions; infer implicit tasks from failing tests, unfinished edits, and "next step" language. Keep specific unfinished tasks specific. Track deferred work separately from NOT DONE. Classify: DONE (completed and verified, or no longer needed), PARTIALLY DONE (started but missing implementation, tests, review, commit, push, or confirmation), NOT DONE (not started or only discussed).
Validate against the workspace. Inspect git status before editing and mention it in the checkpoint; read files the prior session touched. Preserve unrelated user changes in a dirty worktree; use a separate worktree or ask before colliding work. If transcript claims conflict with current files, trust current files and report the mismatch.
Continue from the first unfinished step. Do not repeat completed work; follow the established approach and style unless clearly broken. Ask the user only when blocked by missing information or an unsafe choice.
Decide from the user's prompt how far to go after the checkpoint:
Report-only: the ask is what happened, done versus pending, or to check/audit/review a prior session without edits. Stop after the resume report and clear next action.Continue-edit: the ask is to continue, fix, implement, open a PR, or run tests. Report first, then continue from the first unfinished safe step.Quick resume: status report or task breakdown. Prefer a compact source inventory, task classification, and next action.Deep resume: implementation continues, the source is ambiguous, or files may have drifted. Read the full record and current git state, then continue.references/claude-code.mdreferences/codex.mdreferences/cursor.mdreferences/antigravity.mdreferences/opencode.mdreferences/github-copilot.mdreferences/cross-platform.mdBefore continuing execution, report:
## Brief context summary
- Goal: <prior session goal>
- Loaded skill: path=<loaded SKILL.md path or "unknown">; source/version=<version marker or "unknown">
- Source reviewed: <transcript/export/artifact refs>
- Current workspace check: <git status summary and touched-file refs, or why not checked>
- Transcript/current repo mismatches: <none found | claim, transcript ref, current-repo ref, action>
- User deferrals: <none found | deferred scope, user wording, evidence ref, reopen condition>
- Stopping point: <last command, edit, failure, or user pause instruction with evidence>
## Task status breakdown
- DONE: <task> - evidence: <implementation refs>; verification: <test/tool refs or "not recorded">.
- PARTIALLY DONE: <task> - evidence: <started-work refs>; missing: <remaining gap refs>.
- NOT DONE: <task> - evidence: <TODO, failing test, absent artifact, or transcript gap refs>.
## Clear next action
- Next: <first unfinished step to take now>
- Blocked: <no | yes - reason and evidence>
Then continue immediately unless blocked. Evidence rules and the static idempotency contract: references/evidence-and-provenance.md.
DONE or PARTIALLY DONE from a plan alone; status requires evidence of completion or started work.npx claudepluginhub hacktivist123/agent-session-resume --plugin agent-session-resumeProvides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Creates, edits, and optimizes skills for Claude Code, including drafting, evaluating with test prompts, iterating on performance, and improving skill descriptions for better triggering accuracy.