enterprise-search-strategy — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited enterprise-search-strategy (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
The core intelligence behind Tandem search. Transforms a single natural language question into parallel, source-specific searches and produces ranked, deduplicated results.
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 workspaceThen synthesize the results into a single coherent answer.
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 |
From the query, extract:
For each available source, create one or more targeted queries:
Prefer semantic search for:
Prefer keyword search for:
Generate multiple query variants when the topic might be referred to differently:
User: "Kubernetes setup"
Queries: "Kubernetes", "k8s", "cluster", "container orchestration"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:
| 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 |
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)Task search:
text: "API migration"
workspace: [workspace_id]
completed: false (for status queries)
assignee_any: "me" (for "my tasks" queries)Filter mapping:
| Filter | ~~project tracker parameter |
|---|---|
from:sarah | assignee_any or created_by_any |
after:2025-01-01 | modified_on_after: "2025-01-01" |
type:milestone | resource_subtype: "milestone" |
Score each result on these factors (weighted by query type):
| Factor | Weight (Decision) | Weight (Status) | Weight (Document) | Weight (Factual) |
|---|---|---|---|---|
| Keyword match | 0.3 | 0.2 | 0.4 | 0.3 |
| Freshness | 0.3 | 0.4 | 0.2 | 0.1 |
| Authority | 0.2 | 0.1 | 0.3 | 0.4 |
| Completeness | 0.2 | 0.3 | 0.1 | 0.2 |
Depends on query type:
For factual/policy questions:
Wiki/Official docs > Shared documents > Email announcements > Chat messagesFor "what happened" / decision questions:
Meeting notes > Thread conclusions > Email confirmations > Chat messagesFor status questions:
Task tracker > Recent chat > Status docs > Email updatesWhen a query is ambiguous, prefer asking one focused clarifying question over guessing:
Ambiguous: "search for the migration"
→ "I found references to a few migrations. Are you looking for:
1. The database migration (Project Phoenix)
2. The cloud migration (AWS → GCP)
3. The email migration (Exchange → O365)"Only ask for clarification when:
Do NOT ask for clarification when:
When a source is unavailable or returns no results:
If initial queries return too few results:
Original: "PostgreSQL migration Q2 timeline decision"
Broader: "PostgreSQL migration"
Broader: "database migration"
Broadest: "migration"Remove constraints in this order:
Always execute searches across sources in parallel, never sequentially. The total search time should be roughly equal to the slowest single source, not the sum of all sources.
[User query]
↓ decompose
[~~chat query] [~~email query] [~~cloud storage query] [Wiki query] [~~project tracker query]
↓ ↓ ↓ ↓ ↓
(parallel execution)
↓
[Merge + Rank + Deduplicate]
↓
[Synthesized answer]~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.