The whole folder tree for the organization, nested, with the number of apps filed in each folder and the count sitting at the top level. Each node carries the updated_at that mv needs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 cover the safety profile (read-only, idempotent, non-destructive). The description adds genuine behavioral context beyond those annotations: the result is nested, per-folder app counts are included, a top-level count is present, and each node exposes `updated_at` for `mv`. No contradiction with 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?
The entire description is one dense sentence with no filler: it states scope, nesting behavior, the counts, and the `updated_at` detail. It is front-loaded with the most important fact (the whole folder tree) and every clause adds information.
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 parameterless read-only tool with no output schema, the description covers the key return semantics: full tree, nested structure, counts, top-level count, and per-node `updated_at`. It does not specify exact response field names or types, but those details are less critical given the tool's simplicity and annotation coverage.
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 tool has zero parameters, so there is nothing for the description to clarify about inputs. The baseline for a zero-parameter tool is 4, and the description appropriately focuses on the return value rather than parameters.
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 identifies a specific resource ('the whole folder tree for the organization') and the deliverable shape ('nested, with number of apps ... and updated_at'). It is clear, though it relies on the title and context to convey the read action and does not explicitly distinguish itself from sibling `ls`.
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?
Usage is implied: an agent can infer this is for retrieving the full tree when it needs the complete organization structure, especially before `mv` since nodes carry the `updated_at` mv needs. However, there is no explicit when-to-use/when-not-to-use guidance or naming of alternatives such as `ls` for a narrower view.
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.
Most tools target clearly distinct actions and resources, such as app CRUD, versioning, sharing, secrets, and folder operations. A few adjacent tools like read_app, read_app_file, and read_app_version, or update_app and publish_app_version, require careful reading, but their descriptions are explicit enough to prevent serious confusion.
The set mostly uses a verb_noun pattern, with names like create_app, list_secrets, set_app_access, and trash_app. However, Unix-style commands like ls, mkdir, mv, tree, and whoami, plus mixed verbs such as get, read, list, remove, and revoke, break any single consistent convention.
24 tools is on the heavy end of the 16-25 range, and while the platform covers apps, versions, folders, sharing, secrets, logs, and databases, the count feels somewhat large. Each tool has a defined role, but several could potentially be consolidated without losing clarity.
The surface covers the main lifecycle well: creating, reading, updating, versioning, sharing, securing, and organizing apps, plus secrets and database queries. Notable gaps are the lack of a permanent delete or restore tool for trashed apps, and the stated absence of captured function logs, but these are workable limitations rather than dead ends.
