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Unfold It MCP Server

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by Unfold-it

list_goals

List and filter all learner goals in your organization by status, claim status, metadata, assigned learner, or inactivity to track progress and identify at-risk learners.

Instructions

List all goals in your org created via the API.

Filter by goal status (draft, in_progress, completed), claim status (unclaimed, claimed, expired, revoked), metadata tags, assigned learner email, or inactivity (at-risk detection).

Use this to see all learner goals, check progress across a cohort, find unused claim links, or identify learners who have gone inactive.

For aggregate cohort metrics, use get_analytics instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return
offsetNoPagination offset
statusNoFilter by goal status
categoryNoFilter by resource category. Use this to segment ADHD goals from learning goals.
metadataNoFilter by metadata tag(s) in 'key=value' format. Repeatable for AND logic. E.g. ['track=frontend', 'cohort=spring-2026']
claim_statusNoFilter by claim link status
inactive_daysNoReturn only goals with no step activity in the last N days (at-risk detection)
include_stepsNoInclude per-step details (steps[]) for each goal whose plan is ready. Off by default to keep responses lean; set true to render step lists without a get_goal_status call per goal.
assigned_emailNoReturn only the goal assigned to this learner email address
Behavior3/5

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

No annotations provided, so description bears full burden. Discloses that include_steps is off by default for performance, implying a behavioral trade-off. Does not mention pagination limits, default ordering, rate limits, or authentication. Adequate but not comprehensive.

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

Conciseness5/5

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

Five sentences, front-loaded with main purpose, then filters, then use cases, then alternative tool. No redundant information, each sentence earns its place.

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

Completeness4/5

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

Covers filtering options, use cases, and alternative tools. Does not describe output format or ordering, but no output schema exists. Adequate for a list endpoint with 9 optional parameters.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all parameters. Description adds value by explaining 'at-risk detection' for inactive_days, providing example for metadata usage ('track=frontend'), and clarifying benefit of include_steps. Exceeds baseline 3.

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

Purpose5/5

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

Clearly states 'List all goals in your org created via the API.' Identifies the resource (goals) and action (list). Explicitly differentiates from sibling get_analytics by noting 'For aggregate cohort metrics, use get_analytics instead.'

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

Usage Guidelines5/5

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

Provides explicit use cases: 'see all learner goals, check progress across a cohort, find unused claim links, or identify learners who have gone inactive.' Also tells when not to use: 'For aggregate cohort metrics, use get_analytics instead.'

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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