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Update saved progress

mark_progress

Record the learner's progress server-side (shows on their account + syncs across devices). Call when a section is genuinely completed (section_id), or after a boss battle (boss='passed'/'failed', boss_attempt=true), or on a lab status change (lab=...).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labNo
bossNo
courseYes
moduleYes
auth_tokenNo
section_idNo
boss_attemptNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only include destructiveHint=false, so the description adds valuable behavior context: it says progress is stored server-side, appears on the account, and syncs across devices. It also clarifies accepted payload patterns. It does not mention auth requirements or reversibility, but covers the key behaviors for a non-destructive write operation.

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?

Two sentences, front-loaded with core purpose, then compact usage guidance. Every phrase adds value with no redundancy or fluff.

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?

Given the tool has 7 parameters and an output schema, the description covers the main usage contexts (section completion, boss battle, lab change) and parameter patterns. It could mention auth_token and the required course/module fields more explicitly, but the description is sufficiently complete for an AI agent to use the tool correctly in typical scenarios.

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 has 0% description coverage, but the description compensates by explaining the semantics of section_id, boss ('passed'/'failed'), boss_attempt=true, and lab. Course and module are obvious from their names, and auth_token is the only parameter left unexplained. This is a solid compensation effort.

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?

The description uses a specific verb-object pair ('Record the learner's progress server-side') and clearly explains the effect ('shows on their account + syncs across devices'). It distinguishes itself from siblings like get_progress which reads progress, while this tool writes it.

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

Usage Guidelines4/5

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

Provides explicit when-to-use scenarios: 'Call when a section is genuinely completed (section_id), or after a boss battle..., or on a lab status change.' This gives clear context, though it does not explicitly mention when not to use or name alternative tools.

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but a few overlap or share boundaries: get_lesson vs teach_section (lesson vs section), recall_questions vs daily_drill (both spaced recall), and get_recap vs get_progress (both progress summaries). Descriptions generally help, but these pairs could cause misselection.

Naming Consistency4/5

The vast majority follow a verb_noun snake_case pattern (get_outline, begin_course, submit_exam, etc.). Minor deviations include daily_drill (adjective_noun), interview_prep (noun_noun), login, roast, and whoami (single words), but the overall style is consistent and readable.

Tool Count3/5

24 tools is on the heavy side (16-25 feels bloated), though the platform spans courses, exams, interviews, artifacts, and user management, so the breadth is defensible. Some tools could be consolidated (e.g., recall_questions and daily_drill), making it feel slightly over-scoped.

Completeness3/5

Core learner workflows are covered: discover, start, learn, assess, track, and resume. However, descriptions reference missing tools like get_review and save_artifact, creating dead ends. There's also no tool for authoring/managing courses, even though list_courses mentions user-authored courses, leaving notable gaps.

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