Set current status, next steps, and/or description of a project. Call at end_session to keep description current — projects often evolve.
| Name | Required | Description | Default |
|---|---|---|---|
| nextSteps | No | Free text: What comes next? | |
| projectId | Yes | Project ID | |
| description | No | Updated project description — revise if the core purpose or scope has changed this session | |
| statusSummary | No | Free text: Where does the project stand? |
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?
No annotations are provided, so the description carries the burden of explaining behavior. 'Set' implies an update operation, and the parameter descriptions clarify that fields can be revised, but the description does not disclose side effects, overwrite semantics, or whether the update is reversible. This is adequate but not highly transparent.
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 deliver the core action and a practical usage recommendation with no redundant wording. The main function is front-loaded, and the 'call at end_session' guidance earns its place by adding actionable behavior context.
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 update tool with fully documented parameters and no nested objects or enums, the description is sufficient. It explains what the tool updates and when to use it, and the rich schema covers the fields. It does not mention return values, but given the absence of an output schema and the low complexity, that is a minor gap.
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?
Schema description coverage is 100%, so the schema already documents all four parameters with meaningful descriptions. The tool description adds contextual framing about project evolution but no parameter-level details beyond what the schema provides, so the baseline score of 3 is appropriate.
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?
Description clearly states the action ('Set current status, next steps, and/or description') and the resource ('a project'), so an agent knows what the tool does. It does not explicitly contrast with sibling tools like update_task or update_element, so it earns a 4 rather than a 5.
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 gives a concrete usage cue: 'Call at end_session to keep description current.' This provides clear context for when the tool is appropriate, though it does not explicitly state when not to use it or name alternatives.
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 distinct resources (elements, knowledge, tasks, datasets, snapshots), but a few pairs blur boundaries: create_project/init_project both create projects, and pin_knowledge/set_knowledge_relevance both mark importance for future agents. The descriptions help separate them, but misselection is possible without careful reading.
Tool names consistently use snake_case verb_noun and have solid list_/get_/search_ conventions. However creation verbs are inconsistent (add_element vs create_entry vs save_dataset vs init_project), and deletion mixes delete_entry/delete_file with remove_element, making the naming pattern less predictable than it could be.
48 tools is well above the typical well-scoped range, and the set includes many lifecycle variants (create/init/save/add, delete/remove, update/set) that inflate the count. While the server covers a broad domain, the sheer number makes it heavy and harder for an agent to navigate.
The core surfaces (projects, elements, knowledge, timeline, tasks, chats, datasets, snapshots, files) have solid create/read/update coverage, with search and session-handoff tools. Notable gaps exist: read_file references a download path for binary files that no tool provides, and there is no get_entry or delete/archive for projects, datasets, snapshots, or chat sessions.