Read a crew's notice board: every pinned note plus the newest unpinned ones, current as of this call. The board is the crew's shared coordination state — read it before starting work so you act on the latest news, and post what teammates need to know with scalix_crew_board_post.
| Name | Required | Description | Default |
|---|---|---|---|
| crew_id | Yes | Crew id from scalix_crew_list |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds valuable behavioral context by specifying the exact scope of data (pinned and newest unpinned) and noting the data is current as of the call, which is not implied by the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states the function, the second gives usage guidance. It is front-loaded with the core purpose and remains highly readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and full annotations, the description sufficiently covers what the agent needs to know: what the board contains, when to read it, and that it is live. The lack of an output schema is mitigated by the description's clear specification of content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for crew_id is already complete ('Crew id from scalix_crew_list'), so the description adds no additional parameter semantics. With 100% schema coverage, the baseline of 3 is appropriate; the description does not need to repeat parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Read') and resource ('crew's notice board'), clearly stating exactly what is returned: every pinned note plus the newest unpinned ones. This distinguishes it from the sibling tool scalix_crew_board_post, which handles writing to the board.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs when to use this tool ('read it before starting work so you act on the latest news') and even points to the alternative for the opposite action ('post what teammates need to know with scalix_crew_board_post'). This is clear, actionable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are grouped by service prefix and generally target distinct resources/actions. A few execution surfaces could be confused (sandbox_run vs computer_exec vs fn_invoke; build_create vs fn_deploy vs run_deploy), and storage_list is overloaded for both buckets and objects, but descriptions clarify the boundaries well.
The scalix_ prefix plus snake_case is used throughout, and most tools follow <service>_<verb>_<noun>. Minor deviations like scalix_search, scalix_status, and scalix_usage omit a service-domain qualifier, but the overall pattern is predictable and easy to navigate.
53 tools is a very large surface. While the server covers a broad multi-service cloud platform, the count falls well beyond the 25+ threshold and will likely feel overwhelming; many service areas could reasonably be split into separate servers or trimmed.
Several service lifecycles have obvious gaps: the KV store has get/list/set but no delete, storage has upload/download/list but no delete for objects or buckets, functions have deploy/list/invoke but no delete/update, and cron has create but no list/delete. These missing operations create dead ends for agents managing common resources.
