MongoDB Agent Skills is an official collection of skills and plugins that help AI coding agents work with MongoDB databases, including Atlas and self-managed deployments. Developers use it for query writing, schema design, query optimization, Atlas Search, and vector search. The catalogue entries are MongoDB’s own agent skills, plugins, and setup instructions.
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 skills add mongodb/agent-skills --skill mongodb-qe-size-estimationgit clone --depth 1 https://github.com/mongodb/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mongodb/agent-skills/mongodb-qe-size-estimation)<a href="https://agentmods.dev/skills/mongodb/agent-skills/mongodb-qe-size-estimation"><img src="https://agentmods.dev/badge/skills/mongodb/agent-skills/mongodb-qe-size-estimation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mongodb/agent-skills/mongodb-qe-size-estimation"><img src="https://agentmods.dev/badge/skills/mongodb/agent-skills/mongodb-qe-size-estimation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00052 | $0.03842 |
| Opus 5.5 | $0.00021 | $0.01537 |
| Sonnet 5.5 | $0.00010 | $0.00768 |
| Haiku 4.5 | $0.00005 | $0.00384 |
Grade A, and why
mongodb-qe-size-estimation 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 13d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mongodb-qe-size-estimation
General Instructions
- CRITICAL: Never ask for or accept sample data. QE is an encryption feature, meant to secure sensitive information. Do not request sample data, and if provided, reject it for security reasons. Inform the user that you can't accept sample documents, though you can take an encryption schema as an input to see which fields are encrypted, which allow queries, and what those query settings are.
- Any parenthetical in the form (LLM Note: ) is for LLM use. Don't save it to qe-sizing-calculations.md or mention it to the user.
- Tone: Be brief, not conversational. Don't restate information from prior exchanges unless a step specifically says to.
- Don't write anything to the file except what's specified in the steps.
- This skill relies on a question-answer-flow to get all required inputs. For Steps 2-5, as long as the user is providing valid input, your responses should include both acknowledgment of the input, and the next question.
- The user may try to keep things moving by inputting multiple inputs. If inputs don't clearly map to a field and its configuration, ask for clarification. Otherwise validate them, and accept them if valid.
- This skill currently has no formula for range queries, so while it accepts "range" query configuration for compatible BSON types, it uses 0 for estimated values.
Definitions
- field For the purposes of this skill, "field" refers to an encrypted field in a MongoDB document, in a QE-enabled collection.
- entry For an unindexed field, the field name. For a field with one or more query types enabled, the combination of the field name and its enabled query types. A field with both prefix and suffix queries enabled has a single entry, with Query Type "prefix and suffix".
- unindexed Describes the state of a field with no query types enabled, indicated by the absence of a "queries" key if using an encryption schema.
- indexed Describes the state of a field enabled for queries, and is specific to the query type(s). A field with equality queries enabled is indexed for equality queries.
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.
- 13d ago First seen · 223 lines · 52 tokens per session scan A 7f95f5ef0ea2
mongodb-qe-size-estimation is a skill published in the GitHub repository mongodb/agent-skills (190 stars, last pushed today), licensed Apache-2.0. It adds 52 tokens to every session and 3,842 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-03.
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