enterprise-search

Enterprise Search via Glean

When users ask about internal company information that lives in enterprise systems (not the local codebase), use Glean tools to find it.

Tool Naming

See the glean-tools-guide skill for Glean MCP tool naming conventions. Tools follow the pattern mcp__glean_[server-name]__[tool] where the server name is dynamic. Use whatever Glean server is available in your tool list.

When This Applies

Use Glean search when users ask about:

Company policies, guidelines, or procedures
Design documents, RFCs, or specifications
Internal wikis or knowledge base articles
Project documentation or roadmaps
Slack discussions or announcements
Any "where is the doc about X" questions

BE SKEPTICAL

Not every search result is relevant or current. Before presenting results, evaluate:

Relevance Test

Does this actually answer the question, or just contain keywords?
✅ INCLUDE: Directly addresses the query
❌ EXCLUDE: Keyword coincidence, different context

Freshness Test

Is this information current?
✅ CURRENT: Updated in past 6 months
⚠️ AGING: 6-12 months - note the age
❌ STALE: 12+ months - include only with strong warning, or exclude

Authority Test

How reliable is this source?
📗 OFFICIAL: Approved policies, signed-off specs
📙 SEMI-OFFICIAL: Team wikis, shared docs
📕 INFORMAL: Slack discussions, personal notes

Filter Out:

Superseded or deprecated documents
Draft documents presented as final
Keyword matches in unrelated contexts

See confidence-signals skill for how to communicate reliability.

Tool Selection

User Intent	Glean Tool
Find documents, policies, specs	`search`
Complex analysis across sources	`chat`
Read full document content	`read_document`

Query Optimization

Glean understands natural language. Enhance queries with filters when helpful:

# Recent documents
"API documentation updated:past_week"

# By author
"design doc owner:\"Sarah Chen\""

# Date range
"quarterly planning after:2024-01-01"

# Specific app
"authentication RFC app:confluence"

Workflow

Search first: Use search to find relevant documents
Vet results: Apply vetting criteria before presenting
Read for details: Use read_document with URLs from vetted results
Synthesize if complex: Use chat for multi-source analysis

Always Include Quality Signals

When presenting information from Glean, always include:

Document title and URL
Last updated date (with freshness indicator: ✅/<6mo, ⚠️ 6-12mo, ❌ >12mo)
Author (if relevant)
Confidence level (see confidence-signals skill)

This allows users to assess reliability and explore further.

If Nothing Relevant Found

Don't pad with weak results:

No relevant results found for [query].

**What was searched:**
- [Search terms used]

**Suggestions:**
- Try alternative terms: [suggestions]
- Ask in [relevant channel]
- This may not be documented

Relationship to Commands

For comprehensive, structured workflows, suggest the relevant slash command:

/glean-search:search <query> - Quick search with formatted results
/glean-docs:verify-rfc - Compare spec to implementation
/glean-meetings:catch-up - Systematic catch-up after time away