cost-of-work-index
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_work_tasksA | List every task in the Cost of Work Index — the task id, what one unit is, and which AI employee performs it. Call this first when you do not already know the task id you need. |
| get_task_costA | What one unit of a given task costs in a given market — the human cost per unit, the AI cost per unit, and the ratio between them, with the source behind every figure. Markets: |
| estimate_annual_costA | Turn a monthly volume of a task into monthly and annual cost, for a person and for the AI employee, in one market. Use this when someone asks what a workload costs them per year, or what they would save. |
| list_sourcesA | The official statistics behind the human-cost side of the Index — publisher, exact release title, resolvable URL, reference period, and how the published figure became the number used here. Call this when you need to cite or verify a figure. |
| get_cost_of_work_indexA | The complete Cost of Work Index as JSON — every task, every market, every source, plus the caveats. Use this when you need the dataset itself rather than one answer; prefer |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| cost-of-work-index | Per-unit cost of 13 recurring back-office tasks, person vs software, across the United States, Greece and Ukraine, with sources. CC BY 4.0. |
TDQS
Scored across 5 tools
Each tool serves a distinct function: enumerating tasks, fetching a specific cost, computing annual projections, listing sources, and dumping the whole dataset. There is no meaningful overlap; the only similar tools are list_work_tasks and get_cost_of_work_index, but the latter is explicitly for bulk retrieval while the former is a lightweight overview.
All names follow a consistent verb_noun structure with snake_case. The verbs list/get/estimate clearly signal the action, and the nouns match the resource (work_tasks, task_cost, annual_cost, sources, cost_of_work_index). No mixed conventions or vague verbs are present.
With 5 tools, the set is tightly scoped to the server's purpose of querying a cost index. Each tool covers a necessary operation without redundancy or bloat, making the count well-proportioned.
The server appears to be a read-only index, so the surface covers all natural usage patterns: discovering tasks, retrieving single costs, computing annual estimates, citing sources, and obtaining the full dataset. No obvious gaps exist for the intended domain.