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brasco05

Daily Reflection

by brasco05 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install daily-reflection
Description
Daily reflection routine that runs automatically via cron job at 23:59. Analyzes the day, extracts learnings, updates solution memory, detects recurring patt...
README (SKILL.md)

Daily Reflection Skill

Run this reflection fully. No step may be skipped. All outputs are written to memory — not output as chat messages.


STEP 1 — Day Analysis

Load all today's entries from memory (memory_search for "today", current date, active projects).

Answer these questions:

Tasks

  • Which tasks were completed today?
  • Which were started but not finished?
  • Why were unfinished tasks not completed?

Bugs & Issues

  • Which bugs were reported today?
  • Which were solved — how?
  • Which are still open?
  • Which first fix attempts failed — why?

Quality

  • Were there any regressions today?
  • Did I have to revert anything?

Communication

  • What did the user rate positively today?
  • What did the user correct or reject?
  • Were there misunderstandings?

STEP 2 — Extract Learnings

Maximum 5 concrete learnings. Format:

LEARNING:
Situation: [What happened]
Error/Insight: [What was wrong or newly learned]
Better tomorrow: [Concrete behavior change]
Context-Tags: [e.g. NestJS, Auth, Backend, Debugging]
Priority: high / medium / low

STEP 3 — Update Solution Memory

For each non-trivial bug solved today:

{
  "id": "[timestamp]-[short-name]",
  "problem": "[Problem in one sentence]",
  "symptoms": ["[Symptom 1]", "[Symptom 2]"],
  "root_cause": "[The actual cause]",
  "solution": "[What was concretely changed]",
  "code_snippet": "[Optional: key code fix]",
  "context_tags": ["Tag1", "Tag2"],
  "project": "[Project name]",
  "confidence": 0.95,
  "solved_at": "[Date]",
  "time_to_solve_minutes": 0
}

Write to memory under solution_memory/[id].json.


STEP 4 — Pattern Detection (last 7 days)

Check memory_search over last 7 days:

  • Are there recurring errors?
  • Are there task types where time is consistently underestimated?
  • Are there areas where bugs cluster?

Format:

PATTERN DETECTED:
Observation: [What repeats]
Frequency: [X times in Y days]
Countermeasure: [What I will automatically do from now on]

STEP 5 — Write Morning Briefing

Write to memory/morning-briefing.md (overwrite) AND archive as memory/briefings/[tomorrow-date].md:

🌅 MORNING BRIEFING — [Tomorrow's date]

📋 OPEN TASKS (Priority):
1. [Task] — [why important today]
2. [Task]
3. [Task]

🔴 OPEN BUGS:
- [Bug] — [last status]

💡 TODAY'S LEARNINGS (top 3):
- [Learning 1]
- [Learning 2]
- [Learning 3]

⚠️ WATCH OUT TOMORROW:
- [What to pay special attention to]

🎯 FOCUS TOMORROW:
[One sentence on what's most important]

After writing: mkdir -p memory/briefings && cp memory/morning-briefing.md memory/briefings/[tomorrow-date].md


STEP 6 — Write Daily Memory

Write structured summary to memory/YYYY-MM-DD.md (append).

Format:

## 23:59 Reflection

### Completed today
- [Task 1]
- [Task 2]

### Open / In Progress
- [Task]

### What went well
- [Concrete things that worked — code, communication, decisions]

### What went poorly
- [Honest — errors, misunderstandings, bad decisions]

### Learnings
- Situation: [What happened] → Better tomorrow: [Concrete change]

### New Patterns
- If new pattern detected → write to memory/patterns.md
- If no new pattern: "No new patterns"

### Solution Memory Updates
- [ID] — [short description]

REQUIRED: What went well + What went poorly + Learnings must ALWAYS be filled in.


STEP 7 — Memory Cleanup

  • Delete temporary debug entries from today
  • Mark outdated patterns

STEP 8 — Session Quality Score

Rate today's session objectively (0-10):

📊 SESSION QUALITY — [Date]
Helpful: [0-10] — Did the user get what they needed?
Response time: [0-10] — Was I fast and direct?
Errors: [0-10] — How many corrections? (10 = none)
Proactivity: [0-10] — Did I anticipate problems?
Total: [Average]

What lowered quality today: [specific]
What raised it: [specific]

Write to memory/session-quality-log.md (append). If Total \x3C 7 → analyze main reason and write new pattern.

STEP 9 — Evaluate Cron Prompts

Check last outputs of key crons (read archived briefings):

  • Were they relevant? Too long? Too short?
  • If a prompt produced poor results → propose improvement and update via cron tool

OUTPUT RULE

No chat output. Memory-writes only.

Exception: Critical open problem that can't wait → Short message: ⚠️ Reflection done — critical issue: [1 sentence]


SOLUTION MEMORY — CONSULT BEFORE DEBUGGING

BEFORE any debugging attempt:

  1. memory_search("solution_memory [keywords from bug description]")
  2. Relevant solutions found → try these first
  3. No solutions → debug normally, then write to solution memory

BEFORE similar tasks:

  1. memory_search("solution_memory [task-type]")
  2. Similar past tasks → use time estimate and known pitfalls
Usage Guidance
This skill appears coherent and does what it claims: it reads today's memory entries, extracts learnings, updates solution_memory, and writes briefing and log files. Before enabling it nightly, consider: (1) review what kinds of sensitive data exist in your agent memory—this skill will read and persist that content; (2) back up memory or test in an isolated agent session so accidental deletions (it instructs deleting 'temporary debug entries') don't lose important data; (3) confirm you are comfortable with silent writes (SKILL.md forbids normal chat output); (4) check file permissions on the memory directory so only authorized agents/users can read the generated briefings and solution_memory; (5) run a manual test run and inspect created files to ensure formatting and content meet your expectations.
Capability Analysis
Type: OpenClaw Skill Name: daily-reflection Version: 1.0.0 The daily-reflection skill is a legitimate tool designed to automate end-of-day analysis and long-term memory management for OpenClaw agents. It uses standard file operations and memory searches to organize tasks, bugs, and learnings into structured markdown and JSON files within the agent's workspace. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found in SKILL.md or README.md; all instructions are consistent with the stated purpose of building a self-improving feedback loop.
Capability Assessment
Purpose & Capability
The name/description match the SKILL.md steps: analyze today's memory entries, extract learnings, update solution memory, detect patterns, and write morning briefings. The included README and package.json are consistent with an instruction-only skill that manipulates the agent's memory.
Instruction Scope
All runtime instructions operate on agent memory (memory_search and explicit memory file writes/overwrites). This is consistent with the stated purpose. Note: the skill explicitly directs the agent to read 'all today's entries' and to delete 'temporary debug entries' — actions that can read and remove potentially sensitive or useful data. The SKILL.md also enforces 'No chat output' (except one short critical message), which means results are written silently to memory rather than shown in chat.
Install Mechanism
No install spec and no code files to run; the skill is instruction-only. There are no remote downloads or package installs declared.
Credentials
The skill requests no environment variables or credentials. It does, however, require broad access to the agent's memory (search and write). That access is proportionate to a reflection/memory-updating skill, but it's the primary sensitive capability to be aware of.
Persistence & Privilege
The skill is not force-enabled (always: false). It will create and overwrite files under the agent's memory directory, which is appropriate for its function. It does not request system-level persistence or modify other skills' configs.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install daily-reflection
  3. After installation, invoke the skill by name or use /daily-reflection
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Daily Reflection Skill v1.0.0 - Introduces a structured, step-by-step daily reflection routine triggered automatically at 23:59 by a cron job. - Analyzes the day’s completed and ongoing tasks, bugs, quality issues, and communication. - Extracts up to five concrete learnings and updates a dedicated solution memory for non-trivial bugs. - Detects recurring patterns from the last seven days to improve future performance. - Generates a focused morning briefing and appends a detailed daily summary to memory. - Includes session quality self-assessment and memory cleanup actions at the end of every day. - Designed to work entirely via memory operations, with no user chat output except for critical issues.
Metadata
Slug daily-reflection
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Daily Reflection?

Daily reflection routine that runs automatically via cron job at 23:59. Analyzes the day, extracts learnings, updates solution memory, detects recurring patt... It is an AI Agent Skill for Claude Code / OpenClaw, with 184 downloads so far.

How do I install Daily Reflection?

Run "/install daily-reflection" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Daily Reflection free?

Yes, Daily Reflection is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Daily Reflection support?

Daily Reflection is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Daily Reflection?

It is built and maintained by brasco05 (@brasco05); the current version is v1.0.0.

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