Flip a task's state (todo|doing|blocked|done) and optionally update its one-line plan_status. The narrow AI-after-execution path — use this after you do work on a task.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | ||
| task_id | Yes | ||
| plan_status | No |
| Name | Required | Description | Default |
|---|---|---|---|
| task | No | ||
| error | No | ||
| message | No | ||
| upgrade_url | No |
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 establish that this is a mutating, non-idempotent, non-destructive operation. The description adds concrete behavioral detail: it changes the task state and may overwrite or set plan_status, and it is intended specifically for post-execution updates. This is useful value beyond the structured hints.
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 with no filler. The first sentence states the operation and parameter semantics; the second sentence gives usage context. Everything earns its place.
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 three-parameter state-transition tool, the description covers the input semantics, the valid state values, and the specific execution context. An output schema exists, so return-value details do not need to be restated. No critical information is missing.
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?
With 0% schema description coverage, the description carries the parameter-documentation burden. It compensates well for state by listing all valid values and for plan_status by labeling it as a one-line field, while task_id is self-evident from its title. Some detail about plan_status's null behavior is left to the schema default.
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 action — 'Flip a task's state' — and enumerates the exact allowed values (todo|doing|blocked|done), plus the optional plan_status field. This clearly distinguishes it as a focused state-transition tool rather than a general task-update tool.
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 phrase 'narrow AI-after-execution path — use this after you do work on a task' provides a clear trigger condition for when to use the tool. It does not explicitly name or contrast the sibling update_task tool as the alternative for broader edits, so it falls just short of full exclusion 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.
Most tools map cleanly to distinct resource+action pairs: projects, tasks, skills, user rules, memory, and messaging are all clearly separated. The main ambiguity is update_task versus update_task_state, since update_task can also change state and plan_status, though the descriptions do point to the narrow intended use.
The naming is largely consistent verb_noun snake_case: create_project, update_skill, delete_task, list_projects, get_context, save_turn. Minor deviations include recent_messages lacking a verb, remove_user_rule versus delete_* style, and singular user_rule in mutations versus plural user_rules in listing.
With 27 tools, the server is over the typical well-scoped MCP range, even though it covers several domains. Some consolidation is possible, such as folding update_task_state into update_task and reducing the overlapping retrieval/search tools.
The tool set provides strong lifecycle coverage for projects, tasks, skills, and user rules, plus memory retrieval, agent messaging, and onboarding help. Minor gaps exist, like no standalone get_task or list_tasks and no explicit inbox listing, but get_project and get_context largely cover those needs.
