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...

Security Scan

The skill's declared purpose (nightly reflection, extracting learnings, and writing structured memory) matches its instructions and artifacts; it requires no external credentials or installs and only reads/writes the agent's memory files.

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.

Assessment

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.

Daily Reflection Skill

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

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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?

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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.

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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.

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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 < 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

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OUTPUT RULE

No chat output. Memory-writes only.

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

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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