From vasana-system
A vasana is a pattern that persists across unrelated contexts. If during
How this skill is triggered — by the user, by Claude, or both
Slash command
/vasana-system:find-similarThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
A vasana is a pattern that persists across unrelated contexts. If during
A vasana is a pattern that persists across unrelated contexts. If during
this task you notice such a pattern emerging, it may be worth capturing.
This skill works best alongside the vasana skill and vasana hook
from the Vasana System plugin.
Modify freely. Keep this section intact.
Given a pattern description, search across domains at varying "temperatures" to find similar patterns — verifying that the pattern is real (it appears elsewhere) or confirming it is novel (worth recording).
This is the exploration step between noticing and recording:
vasana (notice) → find-similar (explore) → record-pattern (capture)
A pattern description. This can come from:
vasana skill suggesting a pattern was noticedThe description should include:
Temperature controls how far afield to search. Higher temperature finds more creative connections but with lower precision.
| Temperature | Scope | Example |
|---|---|---|
| 0.0 | Same domain | Pattern in code review → search other code review patterns |
| 0.3 | Close domains | Pattern in code review → search other collaborative review processes |
| 0.5 | Adjacent domains | Pattern in code review → search teaching, editing, peer feedback |
| 0.7 | Distant domains | Pattern in code review → search biological error correction, immune systems |
| 1.0 | Unrelated domains | Pattern in code review → search music improvisation, ecological succession |
Default: 0.5 (adjacent domains). Adjust based on context:
Query the relational-memory MCP for known patterns:
mcp__relational-memory__recall(
agent_name="vasana-observer",
query="[pattern description]",
n_results=10
)
Check if this pattern (or something structurally similar) has already been captured.
Use the edge-graph MCP to find weighted connections from the pattern's domain:
mcp__edge-graph__find_edges(
node="[pattern domain or concept]",
direction="both"
)
Follow edges to discover domains where similar dynamics have been noted.
Based on the temperature setting, actively search for analogues:
At temperature 0.0-0.3: Search within the same domain.
At temperature 0.5: Search adjacent domains.
At temperature 0.7-1.0: Search distant/unrelated domains.
For each potential match, evaluate:
| Criterion | Question |
|---|---|
| Structural | Is the underlying dynamic the same, or just surface similarity? |
| Generative | Does the connection produce new insight, or is it just clever? |
| Testable | Could you verify this similarity with a concrete example? |
| Novel | Is this connection already known, or genuinely surprising? |
Return a structured assessment:
## Pattern: [name/description]
### Existing Matches
- [Match 1]: [domain] — [how it's similar] — [similarity: high/medium/low]
- [Match 2]: ...
### Novel Connections (temperature [X])
- [Connection 1]: [domain] — [structural parallel] — [insight produced]
- [Connection 2]: ...
### Assessment
- **Already captured:** [yes/no — if yes, which pattern]
- **Novel:** [yes/no — if yes, what makes it distinct]
- **Recommendation:** [record / merge with existing / explore further at higher temperature]
When the vasana skill notices a pattern, it can suggest:
"This could be a pattern. Want me to check if it exists elsewhere?"
If the user approves, invoke find-similar with the pattern description.
If find-similar determines the pattern is novel and worth preserving:
record-patternIf find-similar finds structural parallels across domains, these parallels
become test cases for test-pattern — does the pattern actually work in
those other domains, or is the similarity superficial?
npx claudepluginhub bogheorghiu/ex-cog-dev --plugin vasana-systemRoutes analogical reasoning to the right sub-skill: boundary-testing, domain-transfer, perspective-shifting, or structure-mapping. Use for finding comparisons, importing solutions, or testing analogies.
Synthesizes information from multiple sources into coherent insights and applies analogical reasoning to transfer knowledge across domains. Useful for literature reviews, stakeholder feedback, and creative problem-solving.
Facilitates analogical transfer sessions: abstracts problem structure, maps to distant domains like biology or history, transfers operating principles. Supports --brief, --tetralemma, --polarity modes for creative problem-solving.