Create Goal
create_goalCreate a goal in a horizon, with optional bottleneck note and lever.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lever | No | ||
| title | Yes | ||
| horizon | Yes | ||
| bottleneckNote | No |
create_goalCreate a goal in a horizon, with optional bottleneck note and lever.
| Name | Required | Description | Default |
|---|---|---|---|
| lever | No | ||
| title | Yes | ||
| horizon | Yes | ||
| bottleneckNote | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / bottleneckNote / descriptionRemoved value: -"Current constraint limiting progress"Input schema / properties / horizon / descriptionRemoved value: -"Goal horizon (the section it appears under)"Input schema / properties / lever / descriptionRemoved value: -"Highest-leverage action right now"Input schema / properties / title / descriptionRemoved value: -"Goal title"Input schema / properties / bottleneckNote / maxLengthAdded value: +5000Input schema / properties / lever / maxLengthAdded value: +5000Input schema / properties / title / maxLengthAdded value: +500Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral context beyond what the annotations already imply. It does not disclose anything about side effects, duplicate handling, return behavior, or prerequisites for creation. Annotations indicate it is a write operation, but the description itself provides no additional transparency.
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?
One sentence with no filler. It front-loads the action and resource, then lists the relevant scope and optional fields efficiently.
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?
The description plus schema is enough to make a syntactically valid call: required title and horizon are in the schema, and horizon has an enum. However, the meaning of lever and bottleneckNote, and the expected return value, are left unspecified, making it merely adequate.
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 0%, so the description must compensate, but it only mentions optional bottleneckNote and lever and does not explain their meaning. It also omits title from the description, leaving required-parameter semantics entirely to the schema.
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?
States a specific verb ('Create') and resource ('a goal'), plus the target container ('in a horizon') and the key optional fields. This clearly distinguishes it from siblings like create_tasks and update_goal.
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: use this when creating a goal. However, it does not explicitly mention when to prefer this over create_tasks or how it differs from update_goal, so guidance remains implicit rather than explicit.
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.
Each tool targets a distinct resource and action: goals, tasks, subtasks, loops, journal, calendar, and stats are cleanly separated. Descriptions include explicit call-order hints (e.g., get_loops before pull_loops) that reduce ambiguity. No two tools appear to do the same thing.
Tool names consistently follow a verb_noun snake_case pattern: create_, get_, update_, delete_, pull_, reorder_, write_. Even non-standard verbs like pull_loops and write_journal fit the same predictable structure, making the API easy to navigate.
Sixteen tools is slightly above the typical well-scoped range, but the coverage justifies it given the multiple domains: goals, tasks, subtasks, loops, journal, calendar, and focus stats. Each tool has a clear purpose, so none feel redundant or padding.
Goals and tasks have full CRUD coverage, and journal read/write plus loop pulling cover important workflows. Minor gaps exist: loops cannot be created, updated, or deleted, and calendar events are read-only, so some agent actions would require workarounds. Overall, the core planning lifecycle is well supported.