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search-strategy

Query decomposition and multi-source search orchestration.

Skill by necboy-eng

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Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

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Skill name
search-strategy
Description
Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.
License
MIT
Instructions
218 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Search Strategy

> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](../../CONNECTORS.md).

The core intelligence behind enterprise search. Transforms a single natural language question into parallel, source-specific searches and produces ranked, deduplicated results.

## The Goal

Turn this:
```
"What did we decide about the API migration timeline?"
```

Into targeted searches across every connected source:
```
~~chat:  "API migration timeline decision" (semantic) + "API migration" in:#engineering after:2025-01-01
~~knowledge base: semantic search "API migration timeline decision"
~~project tracker:  text search "API migration" in relevant workspace
```

Then synthesize the results into a single coherent answer.

## Query Decomposition

### Step 1: Identify Query Type

Classify the user's question to determine search strategy:

| Query Type | Example | Strategy |
|-----------|---------|----------|
| **Decision** | "What did we decide about X?" | Prioritize conversations (~~chat, email), look for conclusion signals |
| **Status** | "What's the status of Project Y?" | Prioritize recent activity, task trackers, status updates |
| **Document** | "Where's the spec for Z?" | Prioritize Drive, wiki, shared docs |
| **Person** | "Who's working on X?" | Search task assignments, message authors, doc collaborators |
| **Factual** | "What's our policy on X?" | Prioritize wiki, official docs, then confirmatory conversations |
| **Temporal** | "When did X happen?" | Search with broad date range, look for timestamps |
| **Exploratory** | "What do we know about X?" | Broad search across all sources, synthesize |

### Step 2: Extract Search Components

From the query, extract:

- **Keywords**: Core terms that must appear in results
- **Entities**: People, projects, teams, tools (use memory system if available)
- **Intent signals**: Decision words, status words, temporal markers
- **Constraints**: Time ranges, source hints, author filters
- **Negations**: Things to exclude

### Step 3: Generate Sub-Queries Per Source

For each available source, create one or more targeted queries:

**Prefer semantic search** for:
- Conceptual questions ("What do we think about...")
- Questions where exact keywords are unknown
- Exploratory queries

**Prefer keyword search** for:
- Known terms, project names, acronyms
- Exact phrases the user quoted
- Filter-heavy queries (from:, in:, after:)

**Generate multiple query variants** when the topic might be referred to differently:
```
User: "Kubernetes setup"
Queries: "Kubernetes", "k8s", "cluster", "container orchestration"
```

## Source-Specific Query Translation

### ~~chat

**Semantic search** (natural language questions):
```
query: "What is the status of project aurora?"
```

**Keyword search:**
```
query: "project aurora status update"
query: "aurora in:#engineering after:2025-01-15"
query: "from:<@UserID> aurora"
```

**Filter mapping:**
| Enterprise filter | ~~chat syntax |
|------------------|--------------|
| `from:sarah` | `from:sarah` or `from:<@USERID>` |
| `in:engineering` | `in:engineering` |
| `after:2025-01-01` | `after:2025-01-01` |
| `before:2025-02-01` | `before:2025-02-01` |
| `type:thread` | `is:thread` |
| `type:file` | `has:file` |

### ~~knowledge base (Wiki)

**Semantic search** — Use for conceptual queries:
```
descriptive_query: "API migration timeline and decision rationale"
```

**Keyword search** — Use for exact terms:
```
query: "API migration"
query: "\"API migration timeline\""  (exact phrase)
```

### ~~project tracker

**Task search:**
```
text: "API migration"
workspace: [workspace_id]
completed: false  (for status queries)
assignee_any: "me"  (for "my tasks" queries)
```

**Filter mapping:**
| Enterprise filter | ~~project tracker parameter |

From necboy-eng/MantisBot, MIT.

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Last commit (this folder)
Feb 23, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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search-strategy skill. Agent Mart. https://agentmart.dev/skills/necboy-eng-search-strategy (last updated 2026-10-24)