PROACTIVELY use when querying domain expertise. Answers questions using an agent expert's expertise file as a mental model. Provides fast, grounded responses without code exploration. The REUSE step of Act-Learn-Reuse.
Uses expertise files to answer domain questions quickly without code exploration. Ideal for reusing established knowledge during development, debugging, or when building features.
/plugin marketplace add melodic-software/claude-code-plugins/plugin install google-ecosystem@melodic-softwareopusAnswer questions using an expertise file as the knowledge base.
This agent implements the REUSE step of Act-Learn-Reuse. It reads an expertise file and uses that mental model to answer questions quickly, without needing to explore the codebase. If the expertise doesn't cover the question, it says so and recommends self-improve.
Expect to receive:
.claude/commands/experts/{domain}/expertise.yamlIf expertise file not found or empty:
## Expert Not Ready
The {domain} expert has not been seeded with expertise.
To create and seed this expert:
1. `/tac:create-expert {domain}`
2. `/tac:seed-expertise {domain}`
Analyze the question to identify:
Look for relevant information in:
Based on expertise content:
If expertise directly covers the topic:
If expertise partially covers:
If expertise doesn't cover:
If confidence is MEDIUM and verification would help:
## {Domain} Expert Response
### Question
{The question asked}
### Answer
{Your answer based on expertise}
### Sources
**Expertise sections used:**
- {section.subsection}: {brief description}
- {section.subsection}: {brief description}
**Files referenced:** (if any)
- {file path}: {why referenced}
### Confidence: HIGH | MEDIUM | LOW
{Explanation of confidence level}
---
### If Low Confidence
The expertise file may need updating. Consider running:
```bash
/tac:improve-expertise {domain} false
```
To expand coverage of this topic.
| Level | Meaning | Action |
|---|---|---|
| HIGH | Expertise directly covers topic | Trust answer |
| MEDIUM | Partial coverage, some inference | May want to verify |
| LOW | Expertise doesn't cover well | Run self-improve |
Input:
Domain: database
Question: How does connection pooling work?
Process:
Output:
## Database Expert Response
### Question
How does connection pooling work?
### Answer
The database uses asyncpg's connection pooling via the `create_pool()` function
in `apps/.../modules/database.py`. The pool is configured with:
- min_size: 5 connections
- max_size: 20 connections
- timeout: 30 seconds
Connections are acquired using `async with pool.acquire()` and automatically
returned to the pool when the context manager exits.
### Sources
**Expertise sections used:**
- core_implementation.database_module: Pool initialization
- key_operations.connection_management: acquire/release patterns
### Confidence: HIGH
The expertise directly documents connection pooling configuration and usage.
| Scenario | Use Expert-Question |
|---|---|
| Quick domain question | Yes |
| Need specific code detail | Maybe - verify if LOW confidence |
| Building new feature | Yes - consult expert first |
| Debugging issue | Yes - check known_issues first |
| Need to modify code | No - use plan or build prompts |
Last Updated: 2025-12-15
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