tree-of-thoughts
Systematic evaluation methodology for finding THE best solution among known options. Explores multiple reasoning paths, scores branches, and prunes low-confidence paths.
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- kimasplund/clawdbot-skills-pack
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- 26. Januar 2026 um 09:44
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- Englisch
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Quellanweisungen · Schreibgeschützte Vorschau- name
- tree-of-thoughts
- description
- Systematic evaluation methodology for finding THE best solution among known options. Explores multiple reasoning paths, scores branches, and prunes low-confidence paths.
- metadata
- {"clawdbot":{"requires":{"env":"[Truncated]"}}}
- user-invocable
- true
# Tree of Thoughts (ToT)
Find THE best solution by systematically exploring and evaluating multiple reasoning paths.
## When to Use
- Clear success criteria exist
- Multiple known options to evaluate
- Need THE best answer (not all options)
- Time permits thorough analysis
## Process
### Phase 1: Branch Generation
Generate 3-5 distinct approaches to the problem:
```
Root Problem
├── Approach A: [description]
├── Approach B: [description]
├── Approach C: [description]
└── Approach D: [description]
```
### Phase 2: Branch Evaluation
Score each branch on defined criteria (1-10):
| Approach | Feasibility | Impact | Risk | Effort | Total |
|----------|-------------|--------|------|--------|-------|
| A | ? | ? | ? | ? | ? |
| B | ? | ? | ? | ? | ? |
| C | ? | ? | ? | ? | ? |
### Phase 3: Pruning
Eliminate branches scoring below threshold (typically 60%):
- Keep top 2-3 branches
- Document why others were pruned
- Note any branches worth revisiting
### Phase 4: Deep Exploration
For remaining branches, explore sub-options:
```
Approach A (Score: 8.2)
├── Variant A1: [refinement]
├── Variant A2: [refinement]
└── Variant A3: [refinement]
```
### Phase 5: Final Selection
Compare top candidates:
1. Weighted scoring against criteria
2. Risk-adjusted evaluation
3. Implementation complexity
4. Select winner with confidence score
## Output Template
```markdown
## ToT Analysis: [Problem]
### Branches Explored
1. **[Approach A]** - [1-line description]
2. **[Approach B]** - [1-line description]
3. **[Approach C]** - [1-line description]
### Evaluation Matrix
| Approach | [Criteria 1] | [Criteria 2] | [Criteria 3] | Score |
|----------|--------------|--------------|--------------|-------|
| A | X/10 | X/10 | X/10 | X.X |
| B | X/10 | X/10 | X/10 | X.X |
| C | X/10 | X/10 | X/10 | X.X |
### Pruned (with reasons)
- [Approach D]: [why eliminated]
### Recommendation
**Winner: [Approach X]**
- Confidence: [high/medium/low]
- Key advantages: [list]
- Risks to monitor: [list]
```
## Example
**Problem**: Choose database for real-time analytics
**Branches**:
1. PostgreSQL with TimescaleDB
2. ClickHouse
3. Apache Druid
4. Elasticsearch
**Evaluation** (criteria: query speed, scalability, ops complexity):
- ClickHouse: 9 + 9 + 7 = 25 ← Winner
- TimescaleDB: 7 + 7 + 9 = 23
- Druid: 8 + 9 + 5 = 22
- Elasticsearch: 6 + 8 + 6 = 20 (pruned)
**Result**: ClickHouse with 83% confidence
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