ia-reflect
/install compound-eng-reflect
Reflect
Success Criteria
- Every mistake/friction point cites the specific moment and its impact
- Improvements are actionable and prioritized (cap defined in step 4)
- Each skill audit proposes measurable changes (not vague suggestions)
- User is asked which items to persist to memory
- If review activity occurred, review-trap patterns are captured to persistent memory, or explicitly marked as "none"
Process
1. Session Review
Scan the full conversation. For each finding, cite the specific exchange (quote or paraphrase) and its impact.
| Category | Signal |
|---|---|
| Mistakes | Wrong outputs, incorrect assumptions, hallucinated facts |
| Friction | Repeated clarifications, verbose responses, misread intent |
| Wasted effort | Work discarded, wrong approaches tried first |
| Wins | Approaches worth repeating, smooth interactions |
Skip one-time typos, external tool failures, and issues outside agent control.
2. Review Activity Scan (if applicable)
If the session included PR or MR review activity in either direction, run this scan before moving on. Skip only if no reviews happened.
Inbound (my code was reviewed): For each review comment received:
- Did I accept it? If yes, what pattern did the reviewer catch that I missed? Is it a recurring blind spot? Capture the one-liner to persistent memory.
- Did I push back? If I was right and the reviewer was wrong, nothing to capture. If I was wrong and had to retract mid-thread, capture what I learned.
Outbound (I reviewed someone else's code): For each comment I authored:
- Was it accepted? Nothing to capture -- good call.
- Was it rejected with a valid counter? That's a review trap. Capture the pattern: what heuristic did I apply that produced a wrong comment?
"No harvestable items" is a valid outcome -- say so explicitly. Don't let the step quietly drop off.
3. Operational Learnings
Before listing improvements, scan the session for operational insights worth preserving. Apply the 5-minute filter: would knowing this save 5+ minutes in a future session? If yes, include it. Examples: a project-specific quirk, a command that failed unexpectedly, an approach that worked better than expected.
4. Improvements
Numbered list of concrete improvements, ranked by impact. Each item: one sentence, imperative, actionable. Cap at 10 items: if more surface, the bottom items are noise -- drop them rather than batching or splitting.
Ask: "Which of these should I remember for future chats?"
Save approved items to memory files at ~/.claude/projects/\x3Cproject-slug>/memory/ (replace \x3Cproject-slug> with the slug matching the current working directory, e.g., -home-ilia-ai-compound-engineering-plugin) using the Write tool with proper frontmatter (see MEMORY.md index).
5. Skill Audit (if skills were used)
For each skill invoked during the session:
A. Self-check gate -- If the skill lacks success criteria + verification loop:
- Add
## Success Criteriaat top (3-5 measurable checks) - Add
## Self-Checkat bottom: "Verify all success criteria are met before presenting output. If not, iterate (max 5 times)."
B. Token efficiency -- Flag: redundant phrasing, mergeable sections, oversized examples, "Claude already knows this" content, inert frontmatter metadata.
C. Other -- Missing edge cases, vague directives (rewrite as measurable criteria or remove), naked negations (add "do Y instead" or remove).
Present proposed changes as diffs. Ask: "Apply these? (all / pick / skip)"
6. Capture Markers
The remember: prefix is the highest-confidence capture signal. When the user writes a message beginning with remember:, treat everything after the colon as a memory candidate — no interpretation required. Save directly to the appropriate memory file with a one-line summary and the user's exact phrasing. Example: remember: we never use Pest, always PHPUnit → save to feedback_phpunit_over_pest.md.
Correction patterns to watch for (lower-confidence, batch these for review at /ia-reflect time):
- "no, use X" / "actually, X" / "don't use Y, use X"
- "stop doing X" / "never X"
- "that's wrong — the right way is..."
- repeated clarifications of the same thing within a session
Optional capture hook: a UserPromptSubmit hook can pattern-match the markers above into ~/.claude/learnings-queue.json as the user types, so /ia-reflect processes the queue deterministically instead of re-scanning the full transcript. Not shipped with this skill; document the convention and leave implementation to users who need it.
7. Pattern Detection
If 2+ similar tasks appear that no existing skill covers, suggest a new skill (1-2 sentence description). Create only after confirmation.
Proactive trigger: When the user corrects you, clarifies the same thing twice, or shows frustration, append: "Tip: Type /ia-reflect when you're ready -- I'll review what we can improve."
Self-Check
Before presenting output, verify all success criteria are met. If any fail, revise (max 5 iterations).
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install compound-eng-reflect - After installation, invoke the skill by name or use
/compound-eng-reflect - Provide required inputs per the skill's parameter spec and get structured output
What is ia-reflect?
Session retrospective and skill audit. Use when asked to reflect, do a retrospective, review lessons learned, audit what went well or wrong, or review sessio... It is an AI Agent Skill for Claude Code / OpenClaw, with 260 downloads so far.
How do I install ia-reflect?
Run "/install compound-eng-reflect" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is ia-reflect free?
Yes, ia-reflect is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does ia-reflect support?
ia-reflect is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created ia-reflect?
It is built and maintained by Ilia Alshanetsky (@iliaal); the current version is v3.0.4.