search-strategy-step-1-identify-query-type
Sub-skill of search-strategy: Step 1: Identify Query Type (+2).
Best use case
search-strategy-step-1-identify-query-type is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of search-strategy: Step 1: Identify Query Type (+2).
Teams using search-strategy-step-1-identify-query-type should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/step-1-identify-query-type/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How search-strategy-step-1-identify-query-type Compares
| Feature / Agent | search-strategy-step-1-identify-query-type | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of search-strategy: Step 1: Identify Query Type (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Step 1: Identify Query Type (+2)
## 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"
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