I’m looking into whether some less-loved strategy games still manage to perform well. Between 2021 and 2023, which strategy title sold over $200 worth of copies despite being the least liked by buyers? If more than one game fits that description, go with the one that earned the most money. I’d like to know which game it is, how well it sold, and how poorly it was rated. This is all based on cloud data from the video game store.
I’m looking into whether some less-loved strategy games still manage to perform well. Between 2021 and 2023, which strategy title sold over $200 worth of copies despite being the least liked by buyers? If more than one game fits that description, go with the one that earned the most money. I’d like to know which game it is, how well it sold, and how poorly it was rated. This is all based on cloud data from the video game store.
---
name: workspace-filesystem
description: The virtual filesystem layout of this workspace.
---
# Virtual Filesystem
You work in a terminal over a virtual filesystem. Read files with shell
commands.
Command output comes back whole, however long. Some files here are large,
so point `grep -r`, `rg`, `find` and `cat` at the directory or file you
need rather than at a whole mount.
| path | what it is |
|---|---|
| `/data` | Your files. |
| `/mongodb` | Your MongoDB databases, read-only; change them with the `mongodb` CLI. |
| `/tmp` | Scratch space, in memory. |
## `/mongodb`
```
/mongodb/
<database>/
database.json
collections/
<collection>/
schema.json
documents.jsonl
views/
<view>/
schema.json
documents.jsonl
```
- `database.json`: `{database: str, collections: list[{name: str}],
views: list[{name: str}]}`
- `schema.json`: `{database: str, name: str, kind: str, validator: dict |
null, fields: list[{path: str, presence: number, types: dict}],
primary_key: str, indexes: list[{name: str, keys: dict, type: str}],
sampled: int}`, read from a sample of `sampled` documents
- `documents.jsonl`: one document per line, in MongoDB Extended JSON: a date
reads as `{"$date": "..."}`| name | workspace-filesystem |
|---|---|
| description | The virtual filesystem layout of this workspace. |
Virtual Filesystem
You work in a terminal over a virtual filesystem. Read files with shell commands.
Command output comes back whole, however long. Some files here are large, so point grep -r, rg, find and cat at the directory or file you need rather than at a whole mount.
| path | what it is |
|---|---|
/data | Your files. |
/mongodb | Your MongoDB databases, read-only; change them with the mongodb CLI. |
/tmp | Scratch space, in memory. |
/mongodb
/mongodb/
<database>/
database.json
collections/
<collection>/
schema.json
documents.jsonl
views/
<view>/
schema.json
documents.jsonldatabase.json: {database: str, collections: list[{name: str}], views: list[{name: str}]}schema.json: {database: str, name: str, kind: str, validator: dict | null, fields: list[{path: str, presence: number, types: dict}], primary_key: str, indexes: list[{name: str, keys: dict, type: str}], sampled: int}, read from a sample of sampled documentsdocuments.jsonl: one document per line, in MongoDB Extended JSON: a date reads as {"$date": "..."}---
name: workspace-commands
description: Use when running commands in this workspace - which commands exist, what they can do, and what the interpreter supports.
---
# Available commands
Python (`python` or `python3`), Perl, JavaScript/Node.js, and TypeScript
runtimes are unavailable. Use the shell commands and task CLIs documented
below; do not probe for or attempt to install other runtimes.
Standard Unix commands, among them:
cat head tail ls find grep wc sort uniq cut tr sed awk
diff tee xargs jq
with pipes, `>` redirection and `$(...)` substitution.
Do not probe the machine with `which`, `type`, `--version`, `env`, `ps`,
`echo $PATH`, `ls /usr/bin` or `cat /usr/bin/<command>`: they tell you
nothing about the task.
A filename with a space in it needs quoting, as it would in any shell.
You can also use `git`.
## mongodb
Use `mongodb <command> '<JSON arguments>'`. Run `mongodb <command> --help`
to get more information.
```sh
mongodb list-collections '{"database":"DATABASE"}'
mongodb list-databases '{}'
mongodb collection-schema '{"database":"DATABASE","collection":"COLLECTION"}'
mongodb find '{"database":"DATABASE","collection":"COLLECTION","filter":{"FIELD":"VALUE"},"limit":10}'
mongodb count '{"database":"DATABASE","collection":"COLLECTION","query":{"FIELD":"VALUE"}}'
mongodb aggregate '{"database":"DATABASE","collection":"COLLECTION","pipeline":[{"$group":{"_id":"$FIELD","total":{"$sum":1}}}]}'
```
| Command | Arguments | Description |
|---|---|---|
| `mongodb list-collections` | `{database: str}` | List all collections for a given database |
| `mongodb list-databases` | `{}` | List all databases for a MongoDB connection |
| `mongodb collection-schema` | `{database: str, collection: str}` | Describe the schema for a collection |
| `mongodb find` | `{database: str, collection: str, filter?: dict, projection?: dict, limit?: number = 10, sort?: dict}` | Run a find query against a MongoDB collection |
| `mongodb count` | `{database: str, collection: str, query?: dict}` | Gets the number of documents in a MongoDB collection using db.collection.count() and query as an optional filter parameter |
| `mongodb aggregate` | `{database: str, collection: str, pipeline: list[dict]}` | Run an aggregation against a MongoDB collection |
## airtable
Use `airtable <command> '<JSON arguments>'`. Run `airtable <command> --help`
to get more information.
```sh
airtable get-record '{"base_id":"BASE_ID","table_name":"TABLE","record_id":"RECORD_ID"}'
```
| Command | Arguments | Description |
|---|---|---|
| `airtable get-record` | `{base_id: str, table_name: str, record_id: str}` | Get a single record by its ID |
## osm-mcp-server
Use `osm-mcp-server <command> '<JSON arguments>'`. Run
`osm-mcp-server <command> --help` to get more information.
```sh
osm-mcp-server get-route-directions '{"from_latitude":FROM_LATITUDE,"from_longitude":FROM_LONGITUDE,"to_latitude":TO_LATITUDE,"to_longitude":TO_LONGITUDE,"mode":"car"}'
osm-mcp-server find-schools-nearby '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":2000}'
osm-mcp-server analyze-neighborhood '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":1000}'
osm-mcp-server find-parking-facilities '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":1000}'
```
| Command | Arguments | Description |
|---|---|---|
| `osm-mcp-server get-route-directions` | `{from_latitude: number, from_longitude: number, to_latitude: number, to_longitude: number, mode?: str = "car"}` | Calculate detailed route directions between two geographic points. |
| `osm-mcp-server find-schools-nearby` | `{latitude: number, longitude: number, radius?: number = 2000, education_levels?: list[str] = null}` | Locate educational institutions near a specific location, filtered by education level. |
| `osm-mcp-server analyze-neighborhood` | `{latitude: number, longitude: number, radius?: number = 1000}` | Generate a comprehensive neighborhood analysis focused on livability factors. |
| `osm-mcp-server find-parking-facilities` | `{latitude: number, longitude: number, radius?: number = 1000, parking_type?: str = null}` | Locate parking facilities near a specific location. |
## clinicaltrialsgov-mcp-server
Use `clinicaltrialsgov-mcp-server <command> '<JSON arguments>'`. Run
`clinicaltrialsgov-mcp-server <command> --help` to get more information.
```sh
clinicaltrialsgov-mcp-server clinicaltrials-get-study '{"nctIds":"NCT00000000","summaryOnly":true}'
clinicaltrialsgov-mcp-server clinicaltrials-list-studies '{"query":{"cond":"CONDITION"},"pageSize":10}'
```
| Command | Arguments | Description |
|---|---|---|
| `clinicaltrialsgov-mcp-server clinicaltrials-get-study` | `{nctIds: str \| list[str], markupFormat?: "markdown" \| "legacy" = "markdown", fields?: list[str], summaryOnly?: bool = false}` | Fetches one or more clinical studies from ClinicalTrials.gov by their NCT IDs. Returns either complete study data or concise summaries for each. |
| `clinicaltrialsgov-mcp-server clinicaltrials-list-studies` | `{query?: {cond?: str, term?: str, locn?: str, titles?: str, intr?: str, outc?: str, spons?: str, id?: str}, filter?: {ids?: list[str], overallStatus?: list["ACTIVE_NOT_RECRUITING" \| "COMPLETED" \| "ENROLLING_BY_INVITATION" \| "NOT_YET_RECRUITING" \| "RECRUITING" \| "SUSPENDED" \| "TERMINATED" \| "WITHDRAWN" \| "UNKNOWN"], geo?: dict, advanced?: str}, fields?: list[str], sort?: list[str], pageSize?: int = 5, pageToken?: str, countTotal?: bool = true}` | Searches for clinical studies using a combination of query terms and filters. Supports pagination, sorting, and geographic filtering. || name | workspace-commands |
|---|---|
| description | Use when running commands in this workspace - which commands exist, what they can do, and what the interpreter supports. |
Available commands
Python (python or python3), Perl, JavaScript/Node.js, and TypeScript runtimes are unavailable. Use the shell commands and task CLIs documented below; do not probe for or attempt to install other runtimes.
Standard Unix commands, among them:
cat head tail ls find grep wc sort uniq cut tr sed awk
diff tee xargs jqwith pipes, > redirection and $(...) substitution.
Do not probe the machine with which, type, --version, env, ps, echo $PATH, ls /usr/bin or cat /usr/bin/<command>: they tell you nothing about the task.
A filename with a space in it needs quoting, as it would in any shell.
You can also use git.
mongodb
Use mongodb <command> '<JSON arguments>'. Run mongodb <command> --help to get more information.
mongodb list-collections '{"database":"DATABASE"}'
mongodb list-databases '{}'
mongodb collection-schema '{"database":"DATABASE","collection":"COLLECTION"}'
mongodb find '{"database":"DATABASE","collection":"COLLECTION","filter":{"FIELD":"VALUE"},"limit":10}'
mongodb count '{"database":"DATABASE","collection":"COLLECTION","query":{"FIELD":"VALUE"}}'
mongodb aggregate '{"database":"DATABASE","collection":"COLLECTION","pipeline":[{"$group":{"_id":"$FIELD","total":{"$sum":1}}}]}'| Command | Arguments | Description |
|---|---|---|
mongodb list-collections | {database: str} | List all collections for a given database |
mongodb list-databases | {} | List all databases for a MongoDB connection |
mongodb collection-schema | {database: str, collection: str} | Describe the schema for a collection |
mongodb find | {database: str, collection: str, filter?: dict, projection?: dict, limit?: number = 10, sort?: dict} | Run a find query against a MongoDB collection |
mongodb count | {database: str, collection: str, query?: dict} | Gets the number of documents in a MongoDB collection using db.collection.count() and query as an optional filter parameter |
mongodb aggregate | {database: str, collection: str, pipeline: list[dict]} | Run an aggregation against a MongoDB collection |
airtable
Use airtable <command> '<JSON arguments>'. Run airtable <command> --help to get more information.
airtable get-record '{"base_id":"BASE_ID","table_name":"TABLE","record_id":"RECORD_ID"}'| Command | Arguments | Description |
|---|---|---|
airtable get-record | {base_id: str, table_name: str, record_id: str} | Get a single record by its ID |
osm-mcp-server
Use osm-mcp-server <command> '<JSON arguments>'. Run osm-mcp-server <command> --help to get more information.
osm-mcp-server get-route-directions '{"from_latitude":FROM_LATITUDE,"from_longitude":FROM_LONGITUDE,"to_latitude":TO_LATITUDE,"to_longitude":TO_LONGITUDE,"mode":"car"}'
osm-mcp-server find-schools-nearby '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":2000}'
osm-mcp-server analyze-neighborhood '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":1000}'
osm-mcp-server find-parking-facilities '{"latitude":LATITUDE,"longitude":LONGITUDE,"radius":1000}'| Command | Arguments | Description |
|---|---|---|
osm-mcp-server get-route-directions | {from_latitude: number, from_longitude: number, to_latitude: number, to_longitude: number, mode?: str = "car"} | Calculate detailed route directions between two geographic points. |
osm-mcp-server find-schools-nearby | {latitude: number, longitude: number, radius?: number = 2000, education_levels?: list[str] = null} | Locate educational institutions near a specific location, filtered by education level. |
osm-mcp-server analyze-neighborhood | {latitude: number, longitude: number, radius?: number = 1000} | Generate a comprehensive neighborhood analysis focused on livability factors. |
osm-mcp-server find-parking-facilities | {latitude: number, longitude: number, radius?: number = 1000, parking_type?: str = null} | Locate parking facilities near a specific location. |
clinicaltrialsgov-mcp-server
Use clinicaltrialsgov-mcp-server <command> '<JSON arguments>'. Run clinicaltrialsgov-mcp-server <command> --help to get more information.
clinicaltrialsgov-mcp-server clinicaltrials-get-study '{"nctIds":"NCT00000000","summaryOnly":true}'
clinicaltrialsgov-mcp-server clinicaltrials-list-studies '{"query":{"cond":"CONDITION"},"pageSize":10}'| Command | Arguments | Description | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
clinicaltrialsgov-mcp-server clinicaltrials-get-study | `{nctIds: str \ | list[str], markupFormat?: "markdown" \ | "legacy" = "markdown", fields?: list[str], summaryOnly?: bool = false}` | Fetches one or more clinical studies from ClinicalTrials.gov by their NCT IDs. Returns either complete study data or concise summaries for each. | ||||||
clinicaltrialsgov-mcp-server clinicaltrials-list-studies | `{query?: {cond?: str, term?: str, locn?: str, titles?: str, intr?: str, outc?: str, spons?: str, id?: str}, filter?: {ids?: list[str], overallStatus?: list["ACTIVE_NOT_RECRUITING" \ | "COMPLETED" \ | "ENROLLING_BY_INVITATION" \ | "NOT_YET_RECRUITING" \ | "RECRUITING" \ | "SUSPENDED" \ | "TERMINATED" \ | "WITHDRAWN" \ | "UNKNOWN"], geo?: dict, advanced?: str}, fields?: list[str], sort?: list[str], pageSize?: int = 5, pageToken?: str, countTotal?: bool = true}` | Searches for clinical studies using a combination of query terms and filters. Supports pagination, sorting, and geographic filtering. |
| Model | VFS | MCP | VFS Tokens | MCP Tokens | Token Reduction Rate |
|---|---|---|---|---|---|
| Claude Opus 5.5 | 1/1 | 1/1 | 27.8k | 80.3k | 65% |
| GPT-6.1 Sol | 1/1 | 1/1 | 24.3k | 29.8k | 19% |
| GPT-5.6 Luna | 1/1 | 1/1 | 66.0k | 42.5k | −55% |
| Claude Haiku 5.5 | 1/1 | 1/1 | 196k | 330k | 41% |
| Gemini 3.8 Flash | 1/1 | 1/1 | 823k | 1.45M | 43% |