StudiePoint AI
Server Details
300+ African scholarships, GPA conversion & 1,700+ visa routes for postgrad students.
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- Healthy
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- Streamable HTTP
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Tool Definition Quality
Score is being calculated. Check back soon.
Available Tools
6 toolscheck_visaAInspect
Check the visa accessibility rating for an African student of a given nationality applying to study in a specific destination country. Returns a rating (green = easy, yellow = moderate, red = difficult/restricted), notes on the visa process, and any important restrictions.
| Name | Required | Description | Default |
|---|---|---|---|
| destination | Yes | Destination country. Examples: 'UK', 'Germany', 'USA', 'Canada', 'Australia', 'France', 'Netherlands', 'Sweden', 'Norway', 'Japan', 'China', 'South Korea', 'Italy', 'Austria', 'Portugal'. | |
| nationality | Yes | The student's nationality. Examples: 'Nigerian', 'Kenyan', 'Ghanaian', 'South African', 'Ethiopian', 'Tanzanian', 'Ugandan', 'Rwandan', 'Senegalese', 'Moroccan', 'Egyptian', 'Zambian', 'Zimbabwean', 'Cameroonian'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions return values but lacks details on behavior (e.g., idempotency, side effects, or error handling). It is 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Front-loaded with purpose and output description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains return format. It is complete for a simple lookup tool, though it could mention prerequisites or error cases. Slightly above average.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with examples. The description adds context (African student) but does not significantly extend meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks visa accessibility for African students, specifying inputs (nationality, destination) and outputs (rating, notes, restrictions). It distinguishes from sibling tools which deal with scholarships and costs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a visa check is needed, but does not explicitly state when to use or not use this tool. No alternatives are mentioned, though siblings are unrelated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_gpaAInspect
Convert a grade from any of 13 African grading systems to the international 4.0 GPA scale used by scholarship applications worldwide. Covers all 54 African countries. Also returns the grade class (e.g. 'First Class Honors') and how the GPA is interpreted in Germany, UK, France, USA/Canada, Australia, Netherlands, and Japan/Korea/China.
| Name | Required | Description | Default |
|---|---|---|---|
| grade | Yes | The grade class or value. For class-based systems use: 'first_class', 'second_upper', 'second_lower', 'third_class', 'pass'. For kenyan letter grades: 'A', 'B+', 'B', 'C+', 'C', 'D'. For percentage systems: '75%', '68', etc. For french_20: 'tres_bien', 'bien', 'assez_bien', 'passable'. For spanish_10: 'matricula', 'notable', 'aprobado'. | |
| scale | Yes | Grading system. nigerian=5.0 scale, kenyan/ghanaian/ethiopian/west_african_4=letter/class, south_african=percentage, tanzanian/ugandan=5.0 class, zimbabwean/rwandan/percentage=%, french_20=20-point (26 Francophone+Lusophone countries), spanish_10=10-point (Equatorial Guinea). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns GPA, grade class, and interpretations for multiple countries. It does not mention side effects or authentication needs, but such details are not expected for a conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured paragraph that front-loads the primary purpose and then details return values and coverage. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description fully explains the return values (GPA, grade class, international interpretations) and thoroughly documents both parameters. It is complete for a grade conversion tool given its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions, but the tool description greatly enhances understanding by providing concrete examples for 'grade' (e.g., 'first_class', 'A', '75%') and explaining the 'scale' values (e.g., 'nigerian=5.0 scale', 'french_20=20-point'). This surpasses what the schema alone offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: converting grades from 13 African grading systems to a 4.0 GPA scale, and also returning grade class and international interpretations. It distinguishes itself from sibling tools (check_visa, estimate_study_costs, etc.) which are unrelated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates when to use this tool—when a grade conversion is needed—but does not explicitly mention when not to use it or list alternatives. However, given that sibling tools are unrelated, the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
estimate_study_costsAInspect
Estimate and compare the total annual cost of studying in one or more countries for an African postgraduate student. Covers 32 destinations: Tier 3 affordable EU (Germany, France, Italy, Austria, Portugal, Poland, Czech Republic, Estonia, Baltic states, Balkans), Tier 2 full-tuition scholarship countries (Netherlands, Belgium, Scandinavian countries, Japan, South Korea, Switzerland), and benchmark high-cost countries (UK, USA, Canada, Australia). Returns annual cost breakdown: tuition, living, flights, health insurance, visa fee, and total. Use scholarship_mode=true to show the self-funding gap when tuition is already covered by a scholarship.
| Name | Required | Description | Default |
|---|---|---|---|
| lifestyle | No | Budget = shared accommodation, public transport, cooking at home. Comfortable = private room, occasional dining out. Default: budget. | |
| degree_level | No | Degree level. Default: masters. | |
| destinations | No | List of country IDs or names to compare. IDs: germany, france, italy, austria, portugal, poland, czech_republic, estonia, latvia, lithuania, romania, slovakia, croatia, hungary, slovenia, bulgaria, greece, netherlands, belgium, ireland, denmark, finland, sweden, norway, switzerland, japan, south_korea, hong_kong, uk, usa, canada, australia. Alternatively use common names: 'Germany', 'UK', 'United States', etc. Leave empty to return all destinations. | |
| scholarship_mode | No | If true, sets tuition to €0 (assuming tuition is covered by scholarship) and shows only living costs, flights, insurance, and visa. Useful for comparing cities when a student already has a tuition scholarship. Default: false. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description discloses behavior: returns cost breakdown (tuition, living, flights, insurance, visa). Explains effect of scholarship_mode. Does not mention auth or rate limits, but adequately describes what the tool does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise but could be more structured; it's a single paragraph. Front-loaded with purpose. Each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, description fully explains return values (cost breakdown). Covers destination tiers, parameter defaults, and special mode. Complete for a 4-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds significant meaning beyond schema: explains lifestyle options, destination IDs vs names, tier classification, default values, and scholarship_mode effect. All 4 parameters are well-covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool estimates and compares total annual cost of studying for African postgraduate students across 32 destinations. Distinguishes from siblings by focusing on cost estimation vs visas, GPA, or scholarships.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on using scholarship_mode to show self-funding gap. Context implies when to use the tool for cost comparison, but does not explicitly mention when not to use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_scholarshipAInspect
Get complete details on a specific scholarship by name or keyword search. Returns: full name, host country, scholarship amount, deadline, minimum GPA, essay type, acceptance rate, visa accessibility, partner universities, application URL, and committee values.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Scholarship name or search keyword. Examples: 'Chevening', 'DAAD', 'Rhodes', 'Fulbright', 'Gates Cambridge', 'Commonwealth', 'Erasmus Mundus', 'MasterCard Foundation', 'Aga Khan', 'Australia Awards', 'MEXT', 'Korea GKS', 'Eiffel'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. Lists return fields but does not disclose potential side effects or limitations (e.g., read-only, auth needs). Adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first states purpose, second lists return fields. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter and no output schema, description adequately describes input and output. Could include error cases or pagination, but not critical for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers parameter fully (100% coverage). Description adds examples and clarifies that the parameter can be a name or keyword, adding value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves complete details on a specific scholarship by name or keyword search. Implicitly distinguishes from 'search_scholarships' (multiple results) and 'match_scholarships' (matching).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Indicates use case: getting details on a single scholarship. Implicitly different from searching or matching, but lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
match_scholarshipsAInspect
Get personalised, ranked scholarship recommendations for an African student based on their full profile. Uses StudiePoint's matching algorithm to score scholarships by GPA fit, field alignment, visa accessibility, deadline urgency, and acceptance rate. Returns top matches with match score, reasoning, and direct application links.
| Name | Required | Description | Default |
|---|---|---|---|
| field | Yes | Student's field of study. | |
| limit | No | Number of top matches to return. Default 5, max 15. | |
| nationality | Yes | Student's nationality (used for visa scoring). | |
| degree_level | No | Degree level sought. | |
| converted_gpa | Yes | Student's GPA already converted to the 4.0 scale. Use convert_gpa first if needed. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It explains the matching algorithm (GPA fit, field alignment, etc.) and the return format (match score, reasoning, links). However, it does not state whether the tool is read-only, requires authentication, has rate limits, or the data source freshness. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, front-loading the core purpose. Each sentence adds value: purpose, algorithm details, and return summary. No fluff or repetition. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description clearly states what is returned ('top matches with match score, reasoning, and direct application links'). It covers the algorithm criteria and required inputs. For a matching tool with 5 parameters and moderate complexity, this is complete and informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 thoroughly. The description adds no new parameter-level details beyond the overall context of how they are used (e.g., nationality for visa scoring). This is acceptable given high coverage, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get personalised, ranked scholarship recommendations for an African student based on their full profile.' It specifies the verb 'Get', the resource 'scholarship recommendations', and the target user. The mention of ranking and scoring differentiates it from sibling tools like search_scholarships (general search) and get_scholarship (single item).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when a full profile is available for an African student needing ranked matches) but does not explicitly contrast with siblings or state when not to use. It also references using convert_gpa first via the schema but not in the description itself. Sibling names provide context, but explicit guidance would improve it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_scholarshipsAInspect
Search StudiePoint's database of 200+ full-ride scholarships and 100+ full-tuition scholarships for African postgraduate students. Filter by destination country, field of study, minimum GPA (4.0 scale), degree level, and tier. Returns scholarship name, country, amount, deadline, minimum GPA, essay type, visa accessibility, and application URL.
| Name | Required | Description | Default |
|---|---|---|---|
| tier | No | 'full_ride' = fully funded (tuition + living + flights). 'full_tuition' = tuition only, student funds living. 'affordable_eu' = low/no-tuition EU universities across 17 countries. | |
| field | No | Field of study. Examples: 'engineering', 'medicine', 'business', 'law', 'sciences', 'arts', 'agriculture', 'public health', 'economics', 'computer science'. | |
| country | No | Destination country. Examples: 'UK', 'Germany', 'USA', 'Canada', 'Australia', 'Netherlands', 'France', 'Japan', 'China', 'South Korea', 'Sweden', 'Norway'. | |
| min_gpa | No | Maximum minimum GPA required (4.0 scale). Only return scholarships the student can qualify for. | |
| degree_level | No | Degree level: 'masters' or 'phd'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that it is a search/filter operation and lists return fields, but does not mention auth requirements, rate limits, side effects, or any behavioral traits beyond what is obvious from a read search.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. First sentence provides scope and audience, second lists filters and return fields. Information is front-loaded and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers database scope, filters, and return fields. Lacks details on pagination, result count, or ordering, but for a search tool with high schema coverage and no output schema, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter has a description. The tool description adds context about the target audience (African postgraduate students) but does not significantly enhance parameter semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches a specific database of scholarships for African postgraduate students, listing filters and return fields. It distinguishes from siblings like get_scholarship (single scholarship details) and match_scholarships (matching service).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (searching scholarships with filters) but does not explicitly contrast with sibling tools like check_visa, convert_gpa, or estimate_study_costs, leaving the agent to infer usage boundaries.
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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