Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/azure/documentdb-agent-kit/query-optimizernpx skills add Azure/documentdb-agent-kit --skill query-optimizergit clone --depth 1 https://github.com/Azure/documentdb-agent-kitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00094 | $0.02416 |
| Opus 5 | $0.00047 | $0.01208 |
| Sonnet 5 | $0.00019 | $0.00483 |
| Haiku 4.5 | $0.00009 | $0.00242 |
Grade A, and why
documentdb-query-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DocumentDB Query Optimizer
When This Skill Is Invoked
Invoke only when the user wants:
- Query/index optimization or performance help
- Why a query is slow or how to speed it up
- Slow queries on their cluster and/or how to optimize them
- Index recommendations or index review
Do not invoke for routine query authoring unless the user has requested help with optimization, slow queries, or indexing.
High Level Workflow
Help with a Specific Query
If the user is asking about a particular query:
- Use
list_indexes(MCP) ordb.<coll>.getIndexes()(mongosh) to get existing indexes on the collection - Use
explain_operation(MCP) or.explain("executionStats")(mongosh) to get explain output with execution stats - Use
find_documents(MCP) ordb.<coll>.findOne()(mongosh) to fetch a sample document to understand the schema
Then make an optimization suggestion based on collected information and best practices from the reference files. Prefer creating an index that fully covers the query if possible.
General Performance Help
If the user wants to examine slow queries or is looking for general performance suggestions (not regarding any particular query):
- Use
list_databases(MCP) orshow dbs(mongosh) to understand the database structure - Use
get_statisticswith scope "collection" (MCP) ordb.collection.stats()(mongosh) to identify large collections - Use
get_statisticswith scope "index" (MCP) ordb.collection.aggregate([{$indexStats:{}}])(mongosh) to check existing index usage - Use
current_ops(MCP) ordb.currentOp()(mongosh) to see currently running operations - Suggest reviewing the most-used collections for missing indexes
MCP Tools Available
When DocumentDB MCP server is connected, these tools are available:
| Tool name (exact) | Description |
|---|---|
list_indexes |
List all indexes on a collection — check if the query can use an existing index |
explain_operation |
Run explain with executionStats for any operation (find, aggregate, count) |
find_documents |
Fetch sample documents to understand schema — use with limit=1 |
get_statistics |
Get collection or index statistics (use scope: "collection" or "index") |
current_ops |
Get currently running database operations |
create_index |
Create a new index (only after user approval) |
drop_index |
Drop an existing index (only after user approval) |
sample_documents |
Sample random documents from a collection |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 279 lines · 94 tokens per session scan A 5744924df11e
documentdb-query-optimizer is a skill published in the GitHub repository Azure/documentdb-agent-kit (5 stars, last pushed 1mo ago), licensed MIT. It adds 94 tokens to every session and 2,416 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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