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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description confirms it is explanatory, but adds no additional behavioral context beyond that.

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?

One succinct sentence, front-loaded with the core action and examples. No unnecessary details.

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?

The tool is simple: it explains a term. The single parameter is well-defined, and no output schema is needed for an explanatory response.

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?

The schema already fully describes the parameter 'term' with examples. The tool description repeats those examples without adding new semantic information.

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 explains DOAJ metadata terms and gives specific examples (APC, license, etc.), distinguishing it from the sibling search and retrieval tools.

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 purpose strongly implies when to use it, but it does not explicitly contrast with alternatives or state when not to use it.

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

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

The annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) already fully disclose the behavioral profile. The description is consistent with these annotations and adds no contradictory or additional side-effect information, but also does not go beyond them.

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, concise sentence that communicates the essential purpose without any fluff or 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?

The description is clear on its own, but given the presence of sibling tools like search_doaj_journals, it could be more complete by noting that this tool is a specialized subset (filtering for no-fee or diamond OA). Still, the core context is adequate.

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?

All three parameters (query, limit, strict) are fully described in the schema: types, defaults, and purpose. The strict parameter's behavior (AND vs OR) is explicitly explained, and limit has clear bounds. Schema description coverage is 100%.

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 verb 'Find' and the specific resource: no-fee or diamond open-access DOAJ journals. It is unambiguous and directly conveys the tool's purpose.

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 does not explicitly indicate when to use this tool versus the sibling search_doaj_journals or other related tools. While the purpose is specific, guidance on when to prefer this over a general search is missing.

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

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

The description mentions the use of 'local lexical and metadata similarity,' giving some insight into the matching method. However, it does not describe any side effects or return behavior beyond the read-only nature already indicated by annotations.

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, concise sentence that avoids redundancy. It is appropriately brief for its purpose.

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 the simplicity of the tool (three parameters, no output schema), the description provides the core idea but omits details about the returned data format or how similarity is scored. This is a minor gap but not critical for basic usage.

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?

The schema already provides detailed descriptions for all three parameters, covering limit, title, and abstract. The description adds no additional semantic information beyond what the schema states.

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: finding similar articles. It is distinct from search because it focuses on similarity, but it does not explicitly differentiate itself from sibling tools like search_doaj_articles.

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 provides no guidance on when to use this tool versus alternatives such as search_doaj_articles or get_doaj_article_by_doi. It does not mention any conditions or use cases.

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

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

The annotations already declare readOnly, openWorld, and idempotent behavior, so the bar for additional disclosure is lower. The description is consistent with these annotations but adds no extra details (e.g., error handling, return format). It neither contradicts nor enriches the behavioral contract.

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, clear sentence with no redundant words or extraneous information. It is well-structured and immediately conveys the tool's function.

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?

For a straightforward lookup tool, the description is complete enough. It identifies the input (DOI) and the expected outcome (looking up an article). While it does not explicitly state what happens if the DOI is not found, this is a common expectation and not a critical gap given the simplicity.

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?

The single parameter 'doi' is fully described in the schema with format examples, yielding 100% schema coverage. The tool description does not add any additional semantic information about the parameter 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 action ('look up'), the resource ('single DOAJ-indexed article'), and the identifier ('by its DOI'). This is specific and distinguishes it from sibling tools like search_doaj_articles (which searches) and get_doaj_journal_by_issn (which retrieves a journal).

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 does not provide any explicit guidance on when to use this tool instead of alternatives. It does not mention that this is the preferred choice when a DOI is already known, nor does it contrast with search-based retrieval. The context of sibling tools is not referenced.

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

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no additional behavioral context such as error handling, rate limits, or what happens if the ISSN is not found. Given the strong annotation coverage, a 3 is appropriate – the description does not contradict annotations but also does not enrich beyond them.

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 sentence with zero wasted words. It front-loads the action ('Look up a single journal') and the essential constraint (by ISSN). Perfectly concise and scannable.

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?

For a single-parameter, read-only lookup tool with no output schema and complete parameter documentation, the description is adequate. It does not explain the return format or absence behavior, but given the simplicity and the sibling context, nothing critical is missing for an agent to call it correctly.

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% and already explains that the parameter is a print or electronic ISSN with format example. The description's mention of 'print or electronic ISSN' merely restates the schema, adding no new meaning. Baseline 3 applies because the schema carries the full parameter documentation.

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?

Description states a specific verb ('Look up'), a precise resource ('a single DOAJ-indexed journal'), and the exact lookup key (ISSN). It clearly distinguishes this tool from the sibling search_doaj_journals and others by specifying a single-record lookup by identifier rather than a broad search.

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 states the usage condition: you must have an ISSN (print or electronic). It does not explicitly mention alternatives or when-not-to-use, but the clarity of the required input makes the context clear. A mention of 'use search_doaj_journals if you don't have an ISSN' would earn a 5, but the current phrasing is sufficient.

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

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior, so no side-effect disclosure is needed. The description adds the meaningful caveat that output is discovery suggestions rather than acceptance predictions, which helps set expectations.

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 sentence that front-loads the action and object. It contains no redundant filler and leaves detailed parameter information to the schema.

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?

With no output schema, the description gives a general sense that results are discovery candidates, and the title clarifies they are journals. It does not specify the result structure such as journal names or metadata, but for a recommendation tool this is mostly sufficient; slightly more detail could improve completeness.

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?

The input schema covers all 6 parameters with descriptive comments, including guidance like 'Pass the full text, not keywords' and 'not an ISO code', so schema description coverage is 100%. The main description adds no extra per-parameter semantics beyond this, warranting the baseline score.

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 suggests discovery candidates for a manuscript abstract or topic and explicitly disclaims acceptance prediction. It is somewhat less explicit about the resource being DOAJ journals, though the title and name make that unambiguous; it does not fully differentiate from sibling search tools.

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 provides use context ('for a manuscript abstract or topic') and an explicit when-not ('not an acceptance prediction'). It does not name sibling tools or specify when to prefer structured search or diamond-OA filters, so it falls slightly short of fully explicit alternative guidance.

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

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

Annotations already cover safety (readOnly, idempotent, non-destructive) and open-world behavior. The description adds a note about lexical relevance but does not elaborate on result ordering, pagination, or empty-result behavior, which is acceptable given the annotation coverage.

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, focused sentence with no redundant information. It efficiently conveys the purpose without unnecessary detail.

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?

The tool is a straightforward search with no output schema and no nested objects, so the description is largely complete. It does not explicitly mention that results are a list of articles, but this is inferred from the tool name and purpose; minor gap.

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?

The input schema covers all three parameters (query, limit, strict) with clear descriptions. The tool description adds no extra parameter context beyond the schema, so a 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 action (Find), the resource (DOAJ-indexed articles), and the method (lexical relevance and metadata preferences). It distinguishes this tool from siblings like search_doaj_journals and get_doaj_article_by_doi.

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 provides no explicit guidance on when to use this tool versus alternatives. While the lexical relevance hint implies keyword search, it does not differentiate from search_doaj_journals or other article-related tools, leaving the selection largely to inference.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description does not contradict these and adds useful context about lexical relevance and metadata filtering. No side effects or destructive behavior are implied.

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 concise sentence with no redundant wording. It conveys the essential purpose efficiently.

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?

The description is complete enough for a simple search tool with well-documented parameters and no output schema. It clearly indicates what is found, though it does not spell out exact return fields or explicitly contrast with article-level search.

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 rich parameter descriptions explaining behavior such as country/language fallback ranking and strict OR/AND matching. The one-sentence tool description adds little beyond the schema, so the baseline 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's action ('Find'), the resource ('DOAJ-indexed journals'), and the method ('using lexical relevance and metadata preferences'). This distinguishes it from sibling tools that search articles or focus on diamond OA journals.

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 does not explicitly say when to use this tool versus alternatives such as search_doaj_articles or find_diamond_oa_journals. The purpose is clear, but there is no direct guidance on selection criteria among the sibling tools.

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