Ai session tools

AI Session Tools

Search, recover, and analyze AI session histories across Claude Code, AI Studio, and Gemini CLI.

Invoke this skill with: $ai-session-tools, a harness skill picker, or natural language like "find that file from last week", "search sessions for authentication", "recover context from session ab841016". Do not rely on an /ar:* slash command for skill activation; slash-command interception is harness-specific, and current Codex sessions should use skill-native invocation.

After a context compaction, a lost file, or a confusing session — aise finds it. In under a minute you can recover a file the AI (e.g. Claude / Gemini) wrote, restore the sequence of user requests, search every conversation you've ever had, or export a full session to markdown. Works across Claude Code, AI Studio, and Gemini CLI sessions simultaneously.

Full flag reference: aise COMMAND --help

How It Works

1. Find sessions — aise list discovers sessions from ~/.claude/projects/ (Claude Code), AI Studio exports, and Gemini CLI. Filter by --provider, --project, --since.
2. Search and recover — aise messages search, aise files search, aise tools search find content across all sessions. aise files extract recovers files missing from disk.
3. Analyze patterns — aise messages corrections detects where users corrected the AI. aise commands list/context tracks slash command usage. aise analyze runs the full qualitative coding pipeline.
4. Improve from mistakes — Turn recurring corrections into permanent CLAUDE.md rules, skill updates, or hook blocks. Compare before/after correction counts to verify fixes worked (see Workflow 6).

---

Quick Reference

All commands accept --format json for machine-readable output and --full-uuid for full 36-char session IDs.

Goal	Action	Command	Key Options
How much history is indexed?	Count sessions, files, versions	aise stats	--since 7d --provider claude
Know which session contains the work you need	List all sessions, newest first	aise list	--project P --since 7d --limit 20
Narrow to Claude Code sessions only, excluding AI Studio / Gemini	Filter by provider	aise list --provider claude	--since --until --full-uuid
What did the user ask for in this session?	User request sequence — primary context signal	aise messages get SESSION_ID --type user	--limit 10
Restore the full conversation context	Every message in a session	aise messages get SESSION_ID	--type user|assistant --limit 10
See what the user was asking for across recent sessions	User messages from the last N days	aise messages search "" --type user --since 7d	--project P --context 3 --no-compaction
Find when a specific topic was discussed	Search all messages with surrounding context	aise messages search "query"	--type user --context-after 3 --regex --limit 20
What tools did the AI (e.g. Claude / Gemini) call and how often?	Tool counts and files touched	aise messages inspect SESSION_ID	--format json
Reconstruct the exact sequence of events in a session	Chronological timeline with timestamps	aise messages timeline SESSION_ID	--since 14:00 --preview-chars 80
Which sessions touched a specific file?	Search writes/edits by filename pattern	aise files search --pattern "name.py"	--min-edits 2 --include-sessions ID --include-extensions py ts
See every version of a file the AI (e.g. Claude / Gemini) produced across sessions	Every saved version with session and date	aise files history filename.py	--export (write versioned files) --stdout (pipe all versions)
Recover a file missing from disk	Print latest saved version to stdout	aise files extract filename.py	--version 3 --restore --output-dir ./backup
Did the AI's (e.g. Claude / Gemini) edits actually land on disk?	Present vs. missing edit check	aise files cross-ref ./file.py	--session ID --format json
See every file change the AI made to a specific file	Search tool calls by filename	aise tools search Write "filename"	aise tools search Edit "file" aise tools search Read
See every shell command the AI ran	Search Bash calls by substring	aise tools search Bash "git commit"	--format json --limit 20
Recover clipboard content the AI prepared	Extract pbcopy content	aise messages extract SESSION_ID pbcopy	--format json
Produce a persistent readable record of a session	Export session to markdown	aise export session SESSION_ID	--output file.md --dry-run
Document a sprint of AI-assisted work	Export last N days to a file	aise export recent 7 --output week.md	--project myproject
Find something that could be in a file or a message	Cross-domain search (aise find is an alias)	aise search --pattern "*.py" --query "error"	--tool Write --query only --pattern only
Identify where the AI (e.g. Claude / Gemini) went wrong and the user had to correct it	Detect correction patterns by category	aise messages corrections	--pattern 'LABEL:regex' --project P --since
Measure how consistently planning workflows were followed	Count planning invocations across sessions	aise messages planning	--commands '/custom,/cmd'
List every slash command invocation with metadata	When/where was each command used?	aise commands list	--command /ar:plannew --ids-only --since 14d
See what happened after a slash command	Context window post-invocation	aise commands context /ar:plannew	--context-after 5 --format json
Pipe session IDs to another command	Composable workflows with xargs	aise list --since 7d --ids-only	| xargs -I{} aise messages get {}
Filter to slash command messages only	Find real command invocations	aise messages search "" --type slash	--since 14d
Search with asymmetric context windows	See what came before/after a match	aise messages search "error" --context-after 5	--context-before 2
Exclude compaction summaries from search	Focus on real messages only	aise messages search "query" --no-compaction
Search with regex pattern	Complex pattern matching with | for OR	aise messages search "forgot|missed" --regex
Filter timeline events by pattern	Grep within a session timeline	aise messages timeline SID --grep "error"	--regex
Identify recurring AI mistakes across all sessions	Qualitative analysis pipeline	aise analyze	--step analyze|graph --org-dir DIR --status --force
Turn recurring mistakes into permanent fixes	Apply corrections to CLAUDE.md, skills, or hooks	See Workflow 6	Decision table: finding → target → example
Verify a fix actually reduced a failure	Compare correction counts before/after	aise messages corrections --since 7d	Compare to --since 30d baseline
Narrow analyze to one provider	Provider goes at root level	aise --provider claude analyze	aise --provider aistudio analyze
Stop indexing sessions from a removed or unwanted directory	Deregister a session source	aise source remove /path/to/dir	aise source disable claude
What date formats work with --since?	Date format examples and shorthands	aise dates

For multi-step tasks, follow a workflow below.

---

Workflows

1. Recover lost context after compaction

# Find the session
aise list --since 7d

# Get the user request sequence — what was being accomplished, without assistant noise
# This is the primary context signal: ordered user intent, compact, no assistant verbosity
aise messages get SESSION_ID --type user

# Read the full conversation if more detail is needed
aise messages get SESSION_ID

# Find files the AI was editing in that session
aise files search --include-sessions SESSION_ID

# Restore a specific file to its original path on disk
aise files extract filename.py --restore

# Export session to markdown for persistent reference
aise export session SESSION_ID --output session-context.md

---

2. Recover a file the AI (e.g. Claude / Gemini) wrote that is missing from disk

# Find which sessions wrote or edited the file
aise files search --pattern "filename.py"

# Every version: how many edits, which sessions, which dates
aise files history filename.py
aise files history filename.py --export   # write versioned files: filename_v1.py, filename_v2.py, ...
aise files history filename.py --stdout   # all versions to stdout for piping

# Preview a specific version
aise files extract filename.py --version 3

# Restore the latest version to its original path on disk
aise files extract filename.py --restore

# Or write to a backup directory instead
aise files extract filename.py --output-dir ./backup

---

3. Audit what the AI (e.g. Claude / Gemini) did in a session

# Find the session
aise list --project myproject

# Tool counts, files touched — quick overview without reading everything
aise messages inspect SESSION_ID

# Chronological event timeline with timestamps
aise messages timeline SESSION_ID

# Read the full conversation
aise messages get SESSION_ID

---

4. Turn recurring AI mistakes into permanent fixes in skills, prompts, and guidelines

Use this to find what the AI gets wrong repeatedly, extract corrections, and turn them into skill rules, CLAUDE.md additions, or hook integrations to prevent recurrence (see Workflow 6).

# Find messages where the user corrected the AI
# Built-in categories: regression, skip_step, misunderstanding, incomplete
aise messages corrections

# Filter to a specific project, session, or date range
aise messages corrections --project myproject --since 2026-01-01
aise messages corrections --session ab841016

# Add a custom pattern to detect a specific failure type (LABEL:regex)
aise messages corrections --pattern 'tool_misuse:you used the wrong'
aise messages corrections --pattern 'context_loss:you forgot'

# Pipe correction session IDs to another command
aise messages corrections --since 14d --ids-only | \
    xargs -I{} aise messages search "you deleted" --session {} --context-after 3

# How often were planning commands used? (add --commands to count custom slash commands)
aise messages planning
aise messages planning --commands '/myteam:plan,/myteam:review'

# Full qualitative analysis across all sessions:
#   - technique taxonomy, error graph, project classification
#   - use output to extract effective prompts, find recurring failure types,
#     build new skills, update CLAUDE.md rules, hook integrations, or skills (see Workflow 6)
aise analyze --status                  # check which stages are stale before running
aise analyze                           # run the full pipeline
aise --provider claude analyze         # scope to one source only (--provider is a root flag)
aise analyze --step analyze            # run one stage: analyze | graph
aise analyze --force                   # re-run all stages regardless of staleness
aise analyze --org-dir ~/my-org        # override output directory for this run

To make custom patterns permanent across all future runs, add them to correction_patterns in the config file — see Workflow 5.

---

5. Make custom failure categories permanent across all future sessions

aise config path    # find the config file location
aise config show    # view all current values
aise config init    # create a starter config if it doesn't exist yet

correction_patterns — persistent failure categories for aise messages corrections. Format: "LABEL:regex" — label names the category, regex matches in message text.

"correction_patterns": [
  "regression:you deleted",
  "regression:you removed",
  "skip_step:you forgot",
  "skip_step:you missed",
  "misunderstanding:that's wrong",
  "incomplete:also need",
  "tool_misuse:you used the wrong tool",
  "context_loss:you forgot what we were working on",
  "overengineered:that's too complex"
]

planning_commands — which slash commands count toward aise messages planning. Add your own project-specific planning commands:

"planning_commands": ["/ar:plannew", "/ar:planrefine", "/ar:planupdate", "/myteam:plan"]

keyword_maps — classify sessions by project, task type, and workflow for aise analyze taxonomy. Empty by default — fill in to get meaningful session categorization:

"keyword_maps": {
  "project_map": {
    "myproject": ["myproject", "my-project", "myproj"]
  },
  "task_categories": {
    "auth": ["login", "jwt", "oauth", "token"],
    "api": ["endpoint", "rest", "graphql"],
    "testing": ["pytest", "unittest", "test suite"]
  }
}

scoring_weights.corrected_bonus (default: 25) — sessions where the user corrected the AI score higher in the aise analyze pipeline, making them more prominent in the output taxonomy. Increase to weight corrected sessions more heavily when looking for improvement signals.

---

6. Act on analysis — turn findings into permanent improvements

After running aise messages corrections or aise analyze, apply what you found. The goal: each recurring failure becomes a rule that prevents it in future sessions.

Where to apply fixes (pick the right target):

Finding	Target	Example
AI uses wrong tool repeatedly	CLAUDE.md rule	"Always use Read tool, never cat"
AI skips a step in workflow	Skill update	Add step to existing skill's workflow
AI runs dangerous command	Hook integration	Add to DEFAULT_INTEGRATIONS in config.py
AI misunderstands domain term	CLAUDE.md definition	"In this project, 'deploy' means..."
AI pattern applies to many projects	New skill	Extract via /claude-skill-builder

CLAUDE.md — add rules from corrections:

# Find what you corrected the AI about most
aise messages corrections --since 30d

# Example output: 5x "you used cat instead of Read"
# → Add to CLAUDE.md:
#   "Never use cat/head/tail in Bash. Use the Read tool instead."

# Example output: 3x "you forgot to run tests"
# → Add to CLAUDE.md:
#   "After every code change, run the test suite before committing."

Rules go in your project's CLAUDE.md (checked into git) or ~/.claude/CLAUDE.md (global). One concrete sentence per rule. Avoid vague guidance — state exactly what to do or not do.

Hook integrations — block dangerous commands:

If corrections show repeated dangerous command usage, add a block:

/ar:globalno 'dangerous-command'   # block globally across sessions

Skills — extract reusable workflows:

When corrections reveal a missing workflow (not just a single rule), create a skill:

/claude-skill-builder

Verify the fix worked:

# After adding a rule, check if the same correction reappears
aise messages corrections --since 7d --pattern 'LABEL:the pattern you fixed'

# Compare before/after counts
aise messages corrections --since 30d   # before: 5 occurrences
# ... wait a week of sessions ...
aise messages corrections --since 7d    # after: 0 occurrences = success

---

7. Composable pipelines — pipe session IDs between commands

Use --ids-only to chain aise commands via xargs for multi-step analysis.

# Find sessions with corrections, then search each for specific patterns
aise messages corrections --since 14d --ids-only | \
    xargs -I{} aise messages search "you deleted" --session {} --context-after 3

# Find sessions using a specific slash command, export each
aise commands list --command /ar:plannew --since 14d --ids-only | \
    xargs -I{} aise export session {} --output {}.md

# List sessions, search each for error patterns
aise list --since 7d --ids-only | \
    xargs -I{} aise messages search "error|failed|bug" --session {} --regex

---

8. Analyze slash command patterns across sessions

Track slash command usage and post-invocation context with commands list and commands context.

# List all slash command invocations (auto-discovers all commands)
aise commands list --since 14d

# Filter to a specific command
aise commands list --command /ar:plannew --since 14d

# See what Claude did after each invocation of a command (context window)
aise commands context /ar:plannew --context-after 5

# JSON output for scripting
aise commands list --format json --since 14d

# Count unique commands used
aise commands list --since 30d --format json | python3 -c "
import json, sys; from collections import Counter
d = json.load(sys.stdin)
print(Counter(r['command'] for r in d).most_common())"

---

Sources

Claude Code sessions are auto-discovered from ~/.claude/projects/. AI Studio and Gemini CLI require configuration:

aise source scan --save                        # scan standard locations; --save writes found paths to config
aise source add /path/to/aistudio              # add AI Studio export directory (type auto-detected)
aise source add /path/to/aistudio --type aistudio  # add with explicit type
aise source add ~/.gemini/tmp --type gemini    # add Gemini CLI directory
aise source remove /path/to/dir               # remove a source directory from config by path
aise source disable aistudio                  # disable AI Studio auto-discovery (also: gemini_cli)
aise source enable aistudio                   # re-enable auto-discovery (also: gemini_cli)
aise source list                              # show all active sources (auto-detected + configured)

---

Configuration

The config file controls persistent failure detection patterns (correction_patterns), planning command tracking (planning_commands), session taxonomy keywords (keyword_maps), and analysis scoring weights — see Workflow 5 for details.

Config file location (priority order):

1. --config /path/config.json CLI flag — per-invocation override
2. AI_SESSION_TOOLS_CONFIG=/path/config.json env var — session-wide override
3. OS default: ~/Library/Application Support/ai_session_tools/config.json (macOS) or ~/.config/ai_session_tools/config.json (Linux)

Override ~/.claude location: --claude-dir /path or CLAUDE_CONFIG_DIR=/path

aise config show                             # view full config + resolved path
aise config path                             # print config file path only
aise config init                             # create default config (safe — errors if file exists)
aise config init --force                     # overwrite existing config
aise --config /custom/path.json config init  # create config at a specific path

---

Date Filtering

Three flags control date ranges on all commands that support them:

Flag	Purpose	Example
--since	Lower bound (inclusive)	--since 7d --since 2026-01-15
--until	Upper bound (inclusive)	--until 2026-03-01
--when	Set both bounds at once — for EDTF period patterns	--when 202X --when 2026-01

Accepted formats (all three flags):

Format	Example	Matches
Duration shorthand	7d 2w 1m 24h	Last N days/weeks/months/hours
ISO date	2026-01-15	That exact day
Partial date	2026-01 2026	All of January 2026 / all of 2026
EDTF unspecified digit	202X 2026-01-1X	2020s decade / Jan 10–19 2026
EDTF interval (--since only)	2026-01/2026-03	Jan through Mar 2026 (sets both bounds)

Use --when for decade/month/partial-date patterns where a single expression sets the full window. Use --since + --until for explicit asymmetric ranges.

Run aise dates for the full reference.

---

Output Formats

All commands support --format / -f:

Format	Use When
table	Default — human-readable in terminal
json	Scripting, piping to jq, programmatic use
csv	Spreadsheet import
plain	Raw text, minimal formatting

---

Session File Location

~/.claude/projects/<ENCODED-PATH>/<SESSION-ID>.jsonl

Path encoding: all non-alphanumeric characters → -

• /Users/alice/myproject → -Users-alice-myproject
• /Users/alice/.claude → -Users-alice--claude (dot → dash)

Each JSONL line is a JSON object with type (user/assistant/system), timestamp, and message containing tool calls and text content.

See references/session-format.md for the full format reference.

---

Full Flag Reference

aise COMMAND --help — every subcommand has a --help flag with full option descriptions.

aise not found? Run autorun --install --force or uv tool install ai-session-tools.