AI-Scholarly-Mode
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
The mode toggling tools (start/stop) and article tools (list/data) are clearly distinct in purpose. However, without detailed descriptions, an agent might confuse 'get_articles_list' with 'get_springer_article_data' if it needs a general list but picks the Springer-specific one.
Naming Consistency2/5Naming styles are inconsistent: 'scholarly-mode-start' uses hyphens and verb-noun order, while 'get_articles_list' and 'get_springer_article_data' use underscores and get-prefix. This mixed convention reduces predictability.
Tool Count5/5With 4 tools, the set is well-scoped for a scholarly mode server: two for mode management and two for article retrieval. No unnecessary tools, and the count is appropriate for the domain.
Completeness4/5The tool set covers the essential lifecycle: enabling/disabling the mode and retrieving article data. Minor gaps exist, such as no search or query refinement tools, but core workflows are supported.
Average 2.7/5 across 4 of 4 tools scored. Lowest: 1.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It fails to mention whether the operation is read-only, destructive, or what the output format is. The agent has no information about side effects, rate limits, or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise but achieves this at the cost of all informative content. Under-specification is not conciseness; every sentence should earn its place, and here there is only a single tautological phrase.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has two parameters, no output schema, and no annotations, the description is woefully incomplete. An agent cannot determine the return format, pagination behavior, or how to form a valid query. The description fills none of the gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about the parameters. 'query' is unexplained (e.g., search syntax, fields) and 'articles_per_page' lacks constraints (e.g., min, max, default). The description adds zero value beyond the bare schema names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
Description 'Get articles list' is a tautology that merely restates the tool name. It does not specify the source, type, or criteria for articles, and fails to distinguish from the sibling tool 'get_springer_article_data' which likely provides article data from a specific source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines provided. The description does not indicate when to use this tool versus alternatives like 'get_springer_article_data' or the scholarly mode tools. The agent receives no context about prerequisites or appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as idempotency, side effects, or required authentication. The name suggests a read operation, but this is not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) but fails to convey essential information. While not verbose, it is under-specified and does not earn its place because it omits critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one required parameter and no output schema, the description is insufficient. It does not explain the input semantics, return type, or any contextual cues, making it hard for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'id' is a string with no further description. Schema description coverage is 0%, and the description adds no meaning such as whether 'id' is a DOI, article number, or other identifier.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get Springer article data' identifies the resource ('Springer article data') and a generic verb ('Get'), but fails to specify what kind of data is retrieved (e.g., metadata, full text). It distinguishes from sibling 'get_articles_list' only by implication, not explicit mention.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'get_articles_list' or when it is appropriate to call. The description does not mention any prerequisites or context, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It reveals that the tool returns a systemPrompt, which is a key behavioral detail. However, it does not explain what 'scholarly mode' entails, what side effects occur (e.g., losing scholarly context), or whether the tool requires any permissions. Transparency is adequate but could be richer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with only two sentences. The first sentence front-loads the core purpose, and the second adds essential information about the return value. No extraneous words, every sentence is valuable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with no parameters, so the description sufficiently covers its purpose and output. However, it does not explain the concept of 'scholarly mode' or how it relates to sibling tools like 'scholarly-mode-start'. For a complete context, some reference to the start tool or mode semantics would be helpful, but the description is still adequate for a minimal tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100% (empty). The description adds meaning beyond the schema by specifying the return value (systemPrompt). This helps an agent understand the tool's output, which the schema does not address. Scores above baseline 3 due to added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Stop scholarly mode'. It uses a specific verb 'stop' and resource 'scholarly mode', and distinguishes itself from its sibling 'scholarly-mode-start' by being the inverse operation. No confusion about its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context by mentioning the returned systemPrompt to use when not in scholarly mode. However, it does not explicitly state when to use this tool versus alternatives (e.g., just ignoring scholarly mode) or mention any prerequisites or conditions. More explicit guidance would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns a systemPrompt for use in scholarly mode, which is the key behavioral output. Although no annotations exist, the description offers clear state information. It could be more explicit about side effects like state reset on repeated calls, but is adequate for a simple toggle.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and followed by the return value. Every word earns its place; no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description explains the tool's purpose and return value. It adequately covers the basic context, though mentioning that the prompt should be used as a system message would improve completeness. Overall, it is sufficient for a simple mode switch.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the baseline is 4. The description correctly reflects this by not mentioning any parameters, and schema coverage is 100%. No additional clarification is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool starts scholarly mode and distinguishes it from the sibling tool scholarly-mode-stop. The verb 'start' and resource 'scholarly mode' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like get_articles_list or scholarly-mode-stop. It lacks context about prerequisites or conditions for starting scholarly mode.
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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