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sg_nus_modules

Search NUS modules by code or title to get module code, title, and credits. Enter a specific module code for full details including description and prerequisites.

Instructions

Search NUS modules by code or title. Returns module code, title, and credits. Use a specific module code for full details including description and prerequisites.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesModule code (e.g. CS2030S) or keyword (e.g. "machine learning")
acad_yearNoAcademic year e.g. 2024-20252024-2025
Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses return behavior (code/title/credits vs full details) and hints at the difference between query types. Yet it omits potential edge cases like no results, multiple matches, or whether full details are only returned for exact code matches. It is informative 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?

Two sentences, front-loaded with action and object, no redundant phrasing. Every word adds value, making it highly efficient.

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?

Given no output schema and no annotations, the description gives a reasonable overview but lacks details about response structure, handling of multiple matches, empty results, or optional acad_year behavior. It covers the main use cases but leaves gaps that an agent might need for robust invocation.

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 coverage is 100% so baseline is 3. The description adds a usage nuance about using a specific module code for full details, which goes slightly beyond the schema. But it doesn't clarify acad_year usage or response format, so value added is modest.

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 states a specific verb 'Search' with a clear resource 'NUS modules' and search criteria ('by code or title'). It distinguishes from sibling sg_ntu_modules by specifying NUS. It also outlines return contents, making the purpose unambiguous.

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?

It clearly implies use for NUS module lookups and gives within-tool guidance: use keyword for broad search, or specific module code for full details. However, it does not explicitly name alternatives or exclusions (e.g., 'for NTU modules, use sg_ntu_modules').

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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