7,153 messages across 1502 sessions | 2025-12-30 to 2026-02-04
At a Glance
What's working: You've developed a sharp workflow of building reusable slash commands like /release and /infra, turning repetitive operational tasks into a permanent toolkit that compounds over time. Your review-driven approach—where you use Claude as a rigorous scorer and comparator against gold standards rather than just a code generator—is a disciplined quality loop that catches real gaps. Impressive Things You Did →
What's hindering you: On Claude's side, it frequently searches in the wrong directories or repos and delivers work that looks complete but misses important details on the first pass, forcing you into correction loops. On your side, Claude often lacks the project context it needs to navigate your multi-repo setup correctly—and sessions frequently end mid-process, suggesting complex workflows could benefit from being broken into smaller, checkpointed steps. Where Things Go Wrong →
Quick wins to try: You're already building slash command skills organically—formalize your most repeated Bash sequences (especially infrastructure queries and release workflows) into custom skills with `/` commands so Claude starts in the right place every time. Also try hooks to auto-run validation checks after edits, which could catch the 'looks done but isn't thorough' problem without you having to manually request re-reviews. Features to Try →
Ambitious workflows: As models get more capable in the next few months, your release notes pipeline could become fully autonomous—parallel agents gathering deployment SHAs across repos, drafting notes against your gold standard, and self-validating before surfacing results, eliminating your current back-and-forth correction loops. Your multi-repo infrastructure work is also a prime candidate for agents that first build a verified map of your project topology, then execute queries and implementations without the wrong-directory misfires that are your biggest friction point today. On the Horizon →
7,153
Messages
+275,889/-66,001
Lines
2000
Files
26
Days
275.1
Msgs/Day
What You Work On
Release Notes & Deployment Tooling~5 sessions
Significant effort was spent building and refining a /release command that generates deployment release notes across multiple service repositories. Claude was used to align the command and templates with a gold standard format, add intermediate JSON data file generation, and iteratively improve summary detail. There was some friction with thoroughness on first passes, requiring re-reviews.
Infrastructure Querying & CLI Skills~3 sessions
The user leveraged Claude to query deployment SHAs across ECS and Lambda services, explore CLI subcommands (qumis), and build reusable /infra command skills. Claude executed shell commands extensively to gather infrastructure data, though permission issues with certain commands caused friction and required retries.
Feature Implementation & Code Changes~3 sessions
Claude was used for plan-driven feature implementation including adding temperature support to multiple files, implementing ASCII tree visualization for schema detection tests, and creating Makefile targets and CLAUDE.md files. These sessions had high success rates with multi-file changes, separate commits, and draft PR creation.
Code Review, Analysis & Ticket Updates~3 sessions
The user asked Claude to review and score command implementations, analyze template interactions with list detection logic, and update Linear tickets with findings. Claude provided detailed explanations and structured feedback, though it occasionally over-explained or jumped into planning mode unprompted.
Data Inspection & Template Refinement~2 sessions
Claude was used to inspect JSON fixture files for unwanted patterns and structural issues, and to write cleaner templates based on analysis findings. These sessions involved heavy use of search and read tools across the TypeScript and Ruby codebases, though some were cut short before full exploration was completed.
What You Wanted
Review And Feedback
58
Infrastructure Query
28
Documentation Generation
22
Code Implementation
19
Update Ticket
18
Skill Creation
14
Top Tools Used
Bash
21859
Read
6203
Edit
4308
Grep
1843
TodoWrite
1595
Write
1055
Languages
TypeScript
4551
Markdown
1806
Ruby
1263
Shell
544
YAML
422
JSON
320
Session Types
Iterative Refinement
74
Single Task
42
Multi Task
38
Exploration
3
How You Use Claude Code
You are a power user running Claude Code at extraordinary scale — 1,502 sessions and nearly 1,000 hours of usage in just over a month, which suggests you have Claude integrated deeply into your daily workflow across multiple repositories. Your dominant interaction pattern is review-and-refine rather than build-from-scratch: your top goal by far is `review_and_feedback` (58 instances), followed by infrastructure queries and documentation generation, with actual code implementation ranking fourth. This tells us you're leveraging Claude primarily as an analyst, reviewer, and automation assistant rather than as a pure code generator. Your heavy use of Bash (21,859 calls) dwarfs everything else, indicating you frequently have Claude execute commands, run tools, and explore systems rather than just reading or editing files. The 827 Task calls and 1,595 TodoWrite calls suggest you've built out custom slash commands and skills (like `/release` and `/infra`) that orchestrate complex multi-step workflows.
Your interaction style is iterative and corrective — you give Claude a task, let it run, then circle back to tighten the output. Multiple sessions show a pattern where Claude's first pass gets you 80% of the way, but you request re-reviews or refinements (e.g., asking Claude to re-review the `/release` command against a gold standard after the first attempt wasn't thorough enough, or requesting a more detailed summary mid-session). You're not afraid to interrupt and redirect when Claude goes off track — you corrected it when it searched the wrong project directory, interrupted over-explanations, and reformulated requests for precision. The friction data shows `wrong_approach` occurred 43 times, yet your satisfaction remains overwhelmingly positive (174 likely satisfied vs. 10 dissatisfied), which means you've developed an efficient rhythm of steering Claude back on course without losing momentum. You work primarily in TypeScript and Ruby across what appears to be a microservices architecture with ECS and Lambda deployments, and you're actively building reusable Claude skills to encode your team's operational workflows — turning one-off queries into repeatable commands.
Key pattern: You operate as a high-volume orchestrator who builds reusable Claude skills and slash commands, primarily using Claude for review, infrastructure queries, and documentation rather than greenfield coding, with a fast interrupt-and-correct style when it drifts.
User Response Time Distribution
2-10s
341
10-30s
905
30s-1m
858
1-2m
738
2-5m
731
5-15m
343
>15m
271
Median: 59.7s • Average: 213.5s
Multi-Clauding (Parallel Sessions)
63
Overlap Events
85
Sessions Involved
7%
Of Messages
You run multiple Claude Code sessions simultaneously. Multi-clauding is detected when sessions
overlap in time, suggesting parallel workflows.
User Messages by Time of Day
Morning (6-12)
1163
Afternoon (12-18)
4282
Evening (18-24)
1278
Night (0-6)
430
Tool Errors Encountered
Other
5385
Command Failed
903
User Rejected
257
File Too Large
24
Edit Failed
16
File Not Found
15
Impressive Things You Did
You're a power user running over 1,500 sessions across roughly five weeks, heavily leveraging Claude Code for release engineering, infrastructure tooling, and code review across a polyglot TypeScript and Ruby codebase.
Building Reusable Slash Command Skills
You're systematically turning repetitive workflows into reusable slash commands and skills, like your /release and /infra commands. By iterating on these with Claude—reviewing against gold standards, refining output formats, and encoding infrastructure queries—you're building a personalized CLI toolkit that compounds in value over time.
Review-Driven Iterative Refinement
Your top goal is review and feedback, and you use Claude as a rigorous reviewer rather than just a code generator. You ask Claude to score commands, compare outputs against gold standards, and surface improvement suggestions—then you follow up to ensure thoroughness, showing a disciplined quality loop that catches gaps the first pass might miss.
Cross-Service Infrastructure Exploration
You effectively use Claude to query deployment state across multiple ECS and Lambda services, inspect fixture files, and run CLI help across subcommands to build a comprehensive understanding of your infrastructure. With nearly 22,000 Bash invocations and heavy use of Grep and Glob, you've turned Claude into a powerful exploration layer over your distributed system.
What Helped Most (Claude's Capabilities)
Good Explanations
67
Multi-file Changes
23
Fast/Accurate Search
23
Proactive Help
22
Correct Code Edits
11
Outcomes
Not Achieved
10
Partially Achieved
26
Mostly Achieved
36
Fully Achieved
27
Unclear
58
Where Things Go Wrong
Your sessions frequently suffer from Claude operating on wrong assumptions about file locations and project structure, leading to wasted cycles and manual corrections.
Wrong directory and repo assumptions
Claude repeatedly searches in incorrect locations for files and repositories, forcing you to interrupt and redirect. You could reduce this by providing explicit file paths or project context upfront in your prompts rather than relying on Claude to discover them.
Claude looked for the release command in the wrong project directory, requiring you to interrupt and redirect it — resulting in a 'not_achieved' session that produced no useful output
Claude had difficulty locating the correct GitHub repo name for the LLM Service, burning extra exploration steps that slowed down your infrastructure query
Insufficient thoroughness on first pass
Claude completes tasks that appear done but miss important details, forcing you to circle back for verification or rework. You could mitigate this by asking Claude to self-verify against specific acceptance criteria before presenting results as complete.
After Claude made extensive edits to align the /release command with the gold standard, you had to re-request a full review because the first pass wasn't thorough enough to match the reference file
The /release preview session ended mid-process while Claude was still gathering data across multiple repos, suggesting the scope of work wasn't properly estimated before starting
Over-eagerness and unsolicited elaboration
Claude jumps into lengthy explanations or planning modes before you've asked for them, prompting you to interrupt and reformulate. You could set explicit expectations like 'just execute, don't explain' or 'wait for my go-ahead before planning' to keep sessions focused.
You interrupted Claude twice in a single session because it was over-explaining or entering plan mode before being asked to, wasting time on unwanted output
You interrupted your first request to reformulate it more precisely, likely because Claude's initial interpretation was heading in a direction you didn't intend
Primary Friction Types
Wrong Approach
43
User Rejected Action
16
Excessive Changes
9
Inferred Satisfaction (model-estimated)
Dissatisfied
10
Likely Satisfied
174
Existing CC Features to Try
Suggested CLAUDE.md Additions
Just copy this into Claude Code to add it to your CLAUDE.md.
Multiple sessions show Claude searching the wrong directory or repo for files (release command, GitHub repo names), requiring user correction and wasting time.
Friction data shows repeated issues: user interrupted Claude for over-explaining/planning when action was expected, and a review pass wasn't thorough enough requiring a re-review request.
Two sessions involved permission-blocked commands causing cascading failures and multiple retry rounds, wasting significant time.
Just copy this into Claude Code and it'll set it up for you.
Custom Skills
Reusable prompts that run with a single /command for repetitive workflows.
Why for you: You're already building skills (/release, /infra) and 14 sessions focused on skill_creation. Formalizing more of your workflows as skills — especially /review and /ticket-update — would eliminate repeated prompting for your top goals (review_and_feedback at 58 sessions, update_ticket at 18).
mkdir -p .claude/skills/review && cat > .claude/skills/review/SKILL.md << 'EOF'
# Review Skill
1. Read the file(s) specified by the user
2. Compare against any referenced gold standard or spec thoroughly — diff every section
3. Score on: completeness, accuracy, style consistency
4. Output a numbered list of specific improvements
5. Do NOT make changes unless asked
EOF
Hooks
Shell commands that auto-run at specific lifecycle events like pre-commit or post-edit.
Why for you: With 4308 Edit and 1055 Write calls across TypeScript and Ruby, you'd benefit from auto-formatting and type-checking on save. This would catch issues before they compound — your friction data shows 43 'wrong_approach' incidents, some of which formatting/type hooks could prevent early.
Run Claude non-interactively from scripts and CI/CD pipelines.
Why for you: Your /release workflow gathers data across multiple service repos and often gets cut short mid-process (multiple partially_achieved sessions). Running the data-gathering phase headlessly would let it complete without babysitting, and you could review the output afterward.
# Run release notes generation headlessly:
claude -p "Run the /release preview for all services. Output the final release notes to release-notes-draft.md" \
--allowedTools "Bash,Read,Grep,Write" \
--output-file release-output.log
New Ways to Use Claude Code
Just copy this into Claude Code and it'll walk you through it.
Review-then-fix is your dominant workflow — optimize it
Structure review requests with explicit comparison criteria upfront to avoid incomplete first passes.
Review_and_feedback is your #1 goal at 58 sessions, yet friction data shows Claude's first review pass isn't always thorough enough, requiring follow-ups. With 67 'good_explanations' successes but 43 'wrong_approach' frictions, Claude is good at explaining but sometimes misses the mark on execution. Providing a checklist or reference file in the prompt forces systematic comparison rather than skimming.
Paste into Claude Code:
Review [FILE] against [REFERENCE_FILE]. For every section in the reference, confirm the implementation matches exactly. Output a table: | Section | Match? | Difference |. Then list concrete fixes needed. Do not make changes yet.
Sessions ending mid-process — break complex work into checkpoints
Use TodoWrite (already your 5th most-used tool) to create explicit checkpoints for multi-step workflows.
Multiple sessions show work cut short: release previews ending mid-gather, skill updates ending mid-edit, JSON inspection incomplete. With 1595 TodoWrite calls you're already tracking tasks, but structuring long workflows with save-points would let you resume cleanly. Ask Claude to write intermediate results to files rather than keeping everything in-context.
Paste into Claude Code:
Before starting, create a todo list of all steps needed. After completing each step, write the intermediate results to a file in ./tmp/ and check off the todo. If interrupted, I should be able to resume by saying 'continue from the todo list'.
Heavy Bash usage suggests automation opportunities
With 21,859 Bash calls (3.5x your next tool), identify the most repeated commands and wrap them as scripts or skills.
Your Bash-to-Edit ratio of ~5:1 suggests a lot of exploration, querying, and running CLI commands rather than just editing code. The infrastructure_query goal (28 sessions) and the qumis --help sessions confirm this. Converting repeated Bash patterns into reusable scripts or Claude skills would reduce per-session overhead and make results more consistent. The /infra skill you started building is exactly the right direction.
Paste into Claude Code:
Analyze my recent bash history and identify the 10 most frequently run command patterns. For each, suggest whether it should become: (a) a shell alias, (b) a Makefile target, (c) a Claude /skill, or (d) left as-is. Output as a table.
On the Horizon
With nearly 1,000 hours of AI-assisted development across 1,500 sessions, your workflow is mature enough to shift from interactive assistance toward autonomous, multi-agent pipelines that run to completion without intervention.
Autonomous Release Notes Pipeline with Validation
Your most frequent goal is review_and_feedback (58 sessions), and release note generation repeatedly stalls mid-process or requires re-review for accuracy. An autonomous workflow could spawn parallel agents to gather deployment SHAs, diff changelogs across repos, draft release notes against your gold standard template, and then self-validate by comparing structure and content before presenting a final result — eliminating the back-and-forth correction loops you're experiencing today.
Getting started: Use the Task tool to orchestrate sub-agents: one for data gathering across repos, one for drafting, and one for validation against your gold standard file. Chain them with TodoWrite checkpoints so each phase completes before the next begins.
Paste into Claude Code:
I need you to autonomously generate release notes for our latest deployment. Work in three phases using sub-tasks:
Phase 1 - Data Collection: Spawn a Task to gather the latest deployment SHAs across all ECS and Lambda services by running the /infra skill. Collect all commit logs between the last release tag and HEAD for each service repo. Write results to a JSON intermediate file.
Phase 2 - Drafting: Using that JSON file, spawn a Task to draft release notes following the exact structure and tone of our gold standard file at [path to gold standard]. Include every service that had changes.
Phase 3 - Validation: Spawn a final Task that compares the draft against the gold standard for structural compliance, completeness (every SHA accounted for), and formatting. Output a checklist of pass/fail criteria. Only present the final draft to me if all checks pass. If any fail, iterate automatically up to 3 times before showing me what's left.
Use TodoWrite to track progress across all phases. Do not ask me questions — make reasonable decisions and document your assumptions in the output.
You have 43 instances of 'wrong_approach' friction — the single biggest pain point — often caused by Claude searching wrong directories or misunderstanding repo structure. Parallel agents that first build a verified map of your project topology, then implement changes while running tests after each edit, could eliminate misdirected work entirely. Each agent would iterate against your test suite autonomously, only surfacing when tests pass or a genuine decision point is reached.
Getting started: Leverage Task for parallel sub-agents combined with Bash to run tests iteratively. Start each implementation session with a mandatory repo-discovery phase that writes a project map to TodoWrite before any code changes begin.
Paste into Claude Code:
I need you to implement the following feature: [describe feature]. Before writing any code, complete these mandatory steps:
1. DISCOVERY (do not skip): Use Glob and Grep to map out the full project structure relevant to this change. Identify all files that import/reference the modules you'll modify. Write a TodoWrite checklist of every file you plan to touch and why.
2. IMPLEMENTATION: For each file change, spawn a separate Task sub-agent. Each sub-agent should:
- Make the edit
- Run the relevant test suite via Bash
- If tests fail, read the failure output, fix the issue, and re-run (up to 5 iterations)
- Only mark its todo item complete when tests pass
3. INTEGRATION: After all sub-agents complete, run the full test suite. If integration tests fail, diagnose which change caused the regression and fix it autonomously.
4. SUMMARY: Show me a final diff summary, test results, and any assumptions you made. Commit only if all tests pass.
Critical rule: If you're unsure which directory or file to target, search first — never guess. If two possible locations exist, investigate both before choosing.
Parallel Infrastructure Query and Skill Builder
Infrastructure queries are your second most common goal (28 sessions), and you're already building reusable skills like /infra and /release. An autonomous skill-generation pipeline could observe your repeated query patterns, propose new slash commands, scaffold them with proper error handling for permission issues (which caused cascading failures in your sessions), and validate them against live infrastructure — turning ad-hoc questions into a permanent, self-healing CLI toolkit.
Getting started: Use Task sub-agents to parallelize: one agent audits your existing skills for gaps, another prototypes new commands with built-in permission-failure fallbacks, and a third tests them against your actual infrastructure using Bash.
Paste into Claude Code:
I want you to analyze my existing Claude Code skills and build new ones autonomously. Follow this process:
1. AUDIT: Read all files in my skills/slash-commands directory. For each existing skill, document what it does, what infrastructure it queries, and any known failure modes. Also review my last 5 session patterns — I frequently ask about deployment SHAs, service status, and cross-repo comparisons.
2. GAP ANALYSIS: Based on my top query patterns (deployment info, service health, repo comparisons, CLI help enumeration), identify 3 skills that don't exist yet but should. Write the analysis to a markdown file.
3. BUILD (parallel): For each proposed skill, spawn a Task sub-agent to:
- Write the skill file following the conventions of my existing skills
- Include robust error handling: if a command fails due to permissions (like 'infra' or 'secrets' subcommands), catch the error, log it, and continue with remaining queries instead of failing entirely
- Add a --dry-run flag that shows what commands would execute without running them
- Test the skill with --dry-run via Bash
4. DOCUMENT: Update my CLAUDE.md with the new available commands and their usage.
Do not ask me to choose between options — build all three proposed skills and let me evaluate them after.
"Claude confidently started reviewing a release command — in the completely wrong project directory — and had to be interrupted and redirected by the user"
During a session where the user wanted improvements to their /release command, Claude began searching and analyzing files in the wrong repo entirely. The user had to step in and correct it, and the session ended with nothing achieved — a humbling moment of confidently walking into the wrong room.