advise

name	advise
description	Solve problems using knowledge base insights - extracts search terms, runs parallel KB queries, synthesizes advice grounded in your own frameworks
argument-hint	<describe your problem or question in natural language>
allowed-tools	["Bash","Read"]
user-invocable	true

Advise

Help solve problems by grounding advice in your accumulated knowledge and frameworks.

Purpose

Turn natural language problems into KB-grounded advice. Fast path: no subagents, no changelogs, no multi-layer expansion.

Problem

$ARGUMENTS

Process

Step 1: Extract Search Terms (no tool calls - just reasoning)

From the problem description, identify 3-4 keyword clusters that would match relevant KB content:

• Core concepts (what domain is this?)
• Related frameworks (what mental models apply?)
• Analogous patterns (what similar problems exist?)

Example:

• Problem: "Should I focus on fundraising or product development?"
• Search terms: decision making tradeoffs, explore exploit, focus prioritization, opportunity cost

Step 2: Parallel Knowledge Retrieval

Run 3-4 searches in parallel (single message, multiple Bash calls):

resources/local-brain-search/run_search.sh "search term 1" --limit 3 --json
resources/local-brain-search/run_search.sh "search term 2" --limit 3 --json
resources/local-brain-search/run_search.sh "search term 3" --limit 3 --json

Step 3: Read Top Insights

From the search results, read 2-3 of the most relevant note files in parallel:

# Use Read tool on the top-scoring, most relevant files

Step 3.5: Check BDG Context (optional, if top results are frameworks)

For any top result that looks like a framework or key insight, check its BDG context:

resources/brain-graph/run_brain_graph.sh inspect "Top Result Name" --json

This reveals: lifecycle phase (is it generative?), staleness (is it still fresh?), and typed edges (what does it drive?). Prioritize generative frameworks over reflective notes. Warn if citing a stale note.

Step 4: Synthesize Advice

Combine the retrieved insights to address the original problem:

• Apply frameworks from the notes to the specific situation
• Cite specific notes: [[Note Title]]
• Highlight tensions or tradeoffs the KB reveals
• Give concrete recommendations grounded in your own thinking
• Prioritize generative notes (lifecycle > 0.6) - these are the user's strongest frameworks

Output Format

## [Problem summary - one line]

**Relevant frameworks from your KB:**
- [[Note 1]] - [how it applies]
- [[Note 2]] - [how it applies]
- [[Note 3]] - [how it applies]

**My take (grounded in your insights):**

[2-4 paragraphs synthesizing advice, citing notes, applying frameworks to the specific problem]

**Key tradeoffs to consider:**
- [Tradeoff 1]
- [Tradeoff 2]

**Bottom line:** [One clear recommendation or framing]

Rules

• NO subagent spawning - all work happens inline
• NO changelog creation - this is conversational, not archival
• NO spreading activation - use static search for speed
• Parallel execution - run all searches in one message, all reads in the next
• Maximum 2 rounds of tool calls - searches (parallel) + reads (parallel)
• Cite your sources - always reference the specific notes used
• Be actionable - don't just dump knowledge, apply it to the problem
• If KB lacks relevant content, say so honestly and offer general reasoning instead