Mines local coding-agent session logs (Claude Code, Codex, Copilot CLI, OpenCode) to build private, evidence-backed work profiles. Use when user explicitly requests profile setup or update.
How this skill is triggered — by the user, by Claude, or both
Slash command
/agentic-awesome-skills:dittoThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Ditto mines only the user's words from real local coding-agent session logs and
Ditto mines only the user's words from real local coding-agent session logs and turns repeated, supported patterns into private work, design, and writing profiles. It keeps dated session receipts, rejects authored rules and memory as source evidence, and requires approval before model-backed mining begins.
This standalone skill routes a compatible, already-installed Ditto runtime. Native namespaced routing is available through the upstream Ditto plugin.
ditto:mine is unavailable and the user already has a compatible Ditto runtime installed.Do not trigger this skill merely because personalization might be useful. Mining requires an explicit user request.
Ask the user for the path to an existing, trusted Ditto runtime, or use the
native upstream plugin when it is already installed. Retain the exact Python 3
executable path as PYTHON3, the runtime path as DITTO_PY, and its matching
MINING_PROMPT.md path. Confirm the installed version and source before use.
Do not download or install executable code as part of this skill. If Ditto is not installed, stop and direct the user to the upstream installation guidance; installation is a separate, explicit decision.
Mine only real user-authored sessions. Never synthesize a profile from
AGENTS.md, CLAUDE.md, memory files, rules files, or a typed self-description.
Run the full-history quality-default preflight:
"$PYTHON3" "$DITTO_PY" plugin preflight
Show the user the valid session count, post-dedupe source tokens, selected source tokens, cache hits, planned worker calls, and planned reducer calls. Wait for explicit approval of this displayed plan before any model-backed work.
If the user explicitly asks for a quick preview, add --preview and say exactly:
Quick preview creates a starter profile from selected history, not the full profile.
Never present preview as the default or as equivalent to the full-history result.
Retain the displayed approval_hash, then prepare with the exact approved mode.
For the full-history plan, run:
"$PYTHON3" "$DITTO_PY" plugin prepare --approved-plan-hash HASH
For an approved quick-preview plan, preserve preview mode explicitly:
"$PYTHON3" "$DITTO_PY" plugin prepare --preview --approved-plan-hash HASH
If the hash changes, show the new plan and obtain approval again. Retain the
returned run_id, assigned segment and report paths, and pack_path.
For every uncached selected segment, run one worker over only that segment and
the per-segment contract in the resolved MINING_PROMPT.md. Cache each JSON
report with plugin cache-report and stop on rejection.
Run one strongest-available reducer over only the validated reports and reducer
contract. Write the complete pack to pack_path, validate it, and activate only
the validated pack with plugin activate.
Run plugin status, render the profile card, and report:
If the current host already has the native Ditto plugin, do not create a competing direct profile installation.
User: run ditto on my coding history
Agent: resolves the pinned runtime, shows the read-only full-history plan, and
waits for explicit cost approval before starting any mining workers.
User: give me a cheap ditto preview first
Agent: runs preflight with --preview, labels it as a starter profile, and waits
for approval of the displayed preview plan.
Problem: No eligible sessions are found.
Solution: Report the supported source locations that were checked and ask whether the user has retained or exported session history.
Problem: The approval hash changed.
Solution: Do not reuse the old approval. Show the updated plan and obtain approval again.
Problem: A cached or reduced report fails validation.
Solution: Stop, preserve the failure evidence, and never activate the incomplete pack.
@agenttrace-session-audit - Use for cost, latency, failure, and health analysis of coding-agent sessions.@agent-memory - Use for explicit persistent knowledge storage rather than evidence-based profile mining.npx claudepluginhub francostino/antigravity-awesome-skills --plugin agentic-bundle-aas-oss-maintainer3plugins reuse this skill
First indexed Jul 16, 2026
Mines local coding-agent session logs (Claude Code, Codex, Copilot CLI, OpenCode) to build private, evidence-backed work profiles. Use when user explicitly requests profile setup or update.
Analyzes Claude Code session logs to extract tool usage stats, thinking blocks, error patterns, debug trajectories, and generate actionable productivity recommendations. Provides cc-session CLI for overviews, timelines, searches.