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hichana

Goal Story MCP Server

by hichana

goalstory_create_goal

Create a new goal to begin the clarification process, then refine it through discussion to ensure it's well-defined and aligned with your aspirations.

Instructions

Begin the goal clarification process by creating a new goal. Always discuss and refine the goal with the user before or after saving, ensuring it's well-defined and aligned with their aspirations. Confirm if any adjustments are needed after creation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesClear and specific title that captures the essence of the goal.
descriptionNoDetailed explanation of the goal, including context, motivation, and desired outcomes.
story_modeNoNarrative approach that shapes how future stories visualize goal achievement.
belief_modeNoFramework defining how the user's core beliefs and values influence this goal.
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions 'creating a new goal' and suggests user interaction, but lacks details on permissions, whether creation is reversible, error handling, or what happens after saving. For a mutation tool with zero annotation coverage, this is insufficient behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two sentences that convey key information without unnecessary fluff. It's front-loaded with the main action ('create a new goal'), though the second sentence could be slightly more streamlined.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool (creates new data) with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or important behavioral aspects like idempotency or side effects, which are critical for an AI agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 parameters (name, description, story_mode, belief_mode) with clear descriptions. The description doesn't add any additional meaning or context about the parameters beyond what the schema provides, meeting the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('create a new goal') and the resource ('goal'), making the purpose evident. However, it doesn't explicitly differentiate this from sibling tools like 'goalstory_update_goal' or 'goalstory_destroy_goal', which would require more specific language about when to create versus modify or delete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning 'begin the goal clarification process' and suggesting discussion with the user, which gives some context. However, it doesn't explicitly state when to use this tool versus alternatives like 'goalstory_update_goal' or provide clear exclusions, leaving room for ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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