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get_concept_progress

Retrieve a learner's concept-level attempts, independent successes, and due review dates to track mastery and schedule spaced review.

Instructions

Return concept-specific attempts, independent successes, and due review dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
learner_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptsYes
schema_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 behavioral burden, yet it only restates output fields (attempts, successes, due dates) that the output schema already documents. It never discloses that this is a read-only operation, whether learner authorization is required, or any scoping/rate constraints.

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?

A single terse sentence with no filler, front-loaded with the verb and the returned content. It earns its place but is arguably too sparse for the ambiguity it faces.

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

Completeness3/5

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

Return values are covered by the existing output schema and the single param is trivial, so the basics are present. However, with no annotations and several overlapping siblings, the description omits the usage routing an agent needs to invoke this tool correctly rather than get_learner_progress.

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 0% and the single parameter (learner_id) is never mentioned in the description. The param name is largely self-explanatory, which keeps this from being worse, but the description does nothing to compensate for the missing coverage (e.g., format, source of the ID).

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?

States a specific verb ('Return') and a clear resource set (concept-specific attempts, independent successes, due review dates). It is distinct from a generic progress tool by the word 'concept-specific', but it never names or differentiates itself from the similarly-scoped sibling get_learner_progress.

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

Usage Guidelines2/5

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

Provides no when-to-use, when-not-to-use, or alternative guidance. With siblings like get_learner_progress and get_due_repertoire_drill clearly overlapping in the learning-progress/review space, the agent has no basis for choosing this tool.

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