hicar-mcp

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by HICAR-Model

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Each tool targets a distinct resource or action, with clear descriptions. The multiple search tools (code_search, search_docs, etc.) could be confused, but their descriptions specify different domains (source code vs. docs vs. model variables), reducing ambiguity.
Naming Consistency3/5
Tool names follow a verb_noun pattern, but there is inconsistency between 'get_' and 'list_' for related resources (e.g., get_model_variable vs. list_model_variables) and some names include 'tool' (generate_namelist_tool) or are noun_noun (server_status). Still, the pattern is mostly predictable.
Tool Count4/5
With 24 tools, the count is on the high side of reasonable, but it is justified by the complexity of the HICAR model domain, covering code, namelist, variables, physics, and documentation aspects without being excessive.
Completeness4/5
The tool set provides comprehensive coverage for namelist generation, validation, variable metadata, physics scheme resolution, documentation, and source code access. Minor gaps exist (e.g., no tool to modify source or run the model), but these are likely out of scope.
Average 3.3/5 across 24 of 24 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under GPL 3.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does mention a fallback from semantic to lexical search, which is good. However, it does not state if the tool is read-only, requires authentication, or any other side effects. The disclosure is useful but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is too short for a tool with three parameters and multiple siblings. It only has two sentences that are front-loaded but do not provide enough information to be useful. More detail is needed to justify its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and zero schema coverage, the description should compensate with thorough information. It only mentions the fallback behavior, leaving parameter meanings, expected return values, and sibling differentiation entirely unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention any of the three parameters (k, kind, query). With 0% schema coverage, the burden falls entirely on the description, and it fails to provide any meaning beyond the parameter names. The agent cannot infer what 'kind' or 'k' represent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs natural-language semantic search over HICAR code and docs, which is a specific verb and resource. However, it does not differentiate from sibling search tools like search_docs or search_model_variables, leaving ambiguity about when to use this one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It does not mention prerequisites, exclusions, or context for use. The fallback behavior is noted but not as a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states a read-like operation but provides no details on side effects, permissions, or the nature of 'contents'. Minimal transparency beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, which is front-loaded but overly minimal. It could benefit from slight expansion to clarify the parameter without becoming verbose.
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 the tool's simplicity (one parameter, no output schema), the description covers the basic purpose. However, it fails to differentiate from sibling tools or provide parameter context, leaving gaps for effective selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single required parameter 'name' with zero description coverage. The description does not explain what 'name' refers to (e.g., a namelist identifier or file), adding no semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Return the contents of an example namelist,' identifying a specific verb and resource. However, it does not differentiate from sibling tools like 'get_namelist_option' or 'explain_namelist', which have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 such as 'list_example_namelists' or 'search_example_namelists'. The description lacks any context about prerequisites or intended use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only mentions substring search. It does not disclose behavior like case sensitivity, partial matching, or result format. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff. It is concise but could be structured to include more information without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and an output schema, the description is incomplete. It does not explain what the tool returns (list of names, full namelists?) or how the substring matching works, leaving ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds 'substring' context to the query parameter but does not explain its syntax or constraints (e.g., required, minimum length). It barely compensates for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Search) and resource (example namelists) with a specific criterion (substring). It distinguishes from sibling tools like list_example_namelists and get_example_namelist, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives such as semantic_search or search_namelist_options. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details. It does not disclose that the tool is read-only, any authentication requirements, rate limits, or what happens when no group is provided (returns all options). The description only states the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, front-loaded with the action. It contains no unnecessary words. However, it could benefit from a slightly fuller explanation without becoming verbose.
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 the tool's low complexity (single optional parameter, output schema exists), the description is adequate but minimal. It does not mention that the output is a list (though implied by 'list') or how results are ordered. The existence of an output schema partially compensates, but a fuller description would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only implicitly mentions the 'group' parameter via 'filtered to one group'. It does not explain what a group is or provide any additional semantics beyond the schema's field name and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list namelist options) and mentions optional filtering by group. It distinguishes from sibling tools like 'list_namelist_groups' (which lists groups) and 'get_namelist_option' (single option), though it could be more explicit about differences from 'search_namelist_options'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. It does not mention prerequisites, typical use cases, or exclusions (e.g., when to use search_namelist_options instead). The optional group filter is implied but not elaborated.
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 provided; the description fails to disclose any behavioral traits such as error handling, side effects, or network dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the core action, but could include more detail without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 required params and no output schema, the description is incomplete—does not explain what 'resolve' returns or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds minimal meaning beyond the schema—only 'scheme name or integer code' without specifying formats, constraints, or examples.
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 clearly states the verb 'resolve' and the resource 'scheme name or integer code within a category', distinguishing it from sibling tools like 'get_physics_schemes' which likely list all schemes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 (e.g., 'get_physics_schemes'). No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It discloses substring search and return format (doc+line refs) but omits whether the tool is read-only, how many results are returned, performance characteristics, or authentication requirements. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, front-loaded with the action. However, its brevity sacrifices critical details like parameter explanation and usage context, which are needed to make the tool usable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 0% parameter coverage and lack of guidelines, the description is incomplete. Even though an output schema exists, the agent lacks essential information to correctly invoke the tool, especially regarding the parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does 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 either parameter—'query' or 'max_results'. The agent must guess that 'query' is the substring and 'max_results' limits output. No compensation for missing schema descriptions.
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 clearly states the tool searches documentation via substring matching and returns document and line references. It distinguishes this from sibling tools like semantic_search (which likely does semantic search) and list_docs (which lists docs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 semantic_search or search_example_namelists. The description does not mention prerequisites, context, or 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior, but it only states what it returns. It omits whether the operation is read-only, error handling for missing pages, or if authentication is required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence. While effective, it could be slightly more detailed without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Missing output schema and annotations, the description leaves gaps: no return format, error behavior, or how name is resolved. For a tool with multiple siblings, more completeness is needed for proper selection.
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?
The description adds context that the name parameter can be a file name or title, which is not present in the schema (0% coverage). However, it does not clarify how the tool distinguishes between the two or the expected format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a documentation page identified by file name or title. This distinguishes it from sibling tools like list_docs (listing) and search_docs (searching), but it does not explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings, nor on how to choose between file name and title for the name parameter. The user must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description offers no behavioral details (e.g., read-only, side effects). For a list operation, it should at least state it is non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded and extremely concise (3 words). While efficient, it misses opportunity to add context.
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 parameters and existence of output schema, the description is minimally adequate but does not explain what the output contains (e.g., list of names or objects).
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?
No parameters exist, so description does not need to elaborate. Baseline 4 is appropriate as the schema already fully covers parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'list' and resource 'example namelists' with qualifier 'bundled', which distinguishes it from search-like siblings. However, it lacks explicit differentiation from 'get_example_namelist'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings like 'search_example_namelists' or 'get_example_namelist'. The agent must infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It mentions 'substring' but does not specify case sensitivity, pagination, result limits, or ordering. For a search tool, these are important gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence of 8 words, but it omits critical details about parameters and behavior. It is too brief to be considered well-structured for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (though not shown), the description should at least hint at return values or fields. It does not mention output format. The missing 'group' parameter explanation and lack of behavioral details make it incomplete for a search tool with 2 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must add meaning. It implies 'query' parameter exists but completely ignores the optional 'group' parameter, leaving its purpose unexplained. The meaning of parameters is insufficiently conveyed.
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 clearly states the verb 'Search', the resource 'namelist options', and the method 'by name/description (substring)', which distinguishes it from sibling tools like list_namelist_options (listing all) and get_namelist_option (retrieving a specific one).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for substring matching but does not explicitly state when to use this tool over alternatives like semantic_search or code_search, nor does it provide exclusions or prerequisites. It is adequate but lacks guidance on context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 a prerequisite but does not disclose other behavioral traits such as whether the operation is read-only, side effects, or error conditions. The description is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, but it could be more structured, e.g., listing parameters or expected behavior. It earns a 4 for being mostly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given 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 incomplete. It does not explain the 'kind' parameter, return format, or error handling, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only adds context for the 'name' parameter ('by name'). The 'kind' parameter is not explained. With low coverage, the description should compensate but does so insufficiently.
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 clearly states the verb 'Find' and resource 'Fortran symbols', and specifies the types (module/subroutine/function/type). It is specific and distinguishes from siblings such as code_search which likely searches general code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a prerequisite ('Requires HICAR_REPO (live mode)') but does not provide guidance on when to use this tool versus alternatives like code_search or other search tools. Usage is implied by the name but not explicitly clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only mentions delegation with use_binary but does not describe whether the tool creates files, requires permissions, or returns data. The lack of output schema or return value description is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no redundancy. The first sentence conveys the core function, the second adds alternative behavior. It is appropriately sized but could benefit from more structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 11 parameters, no schema descriptions, no output schema, and high complexity, the description is insufficient. It lacks details on return values, error handling, and parameter constraints, leaving the agent without enough information to use the tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description must explain parameters. It only mentions 'mode' and 'physics scheme selections' generically, leaving 11 parameters (e.g., mp, sm, lsm) undocumented. The agent cannot know valid values or semantics from the description alone.
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 clearly states it generates a namelist with two modes ('full' or 'minimal') and optional physics scheme selections. This distinguishes it from sibling tools like validate_namelist or explain_namelist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use the 'use_binary' flag but does not compare with alternatives or state when not to use this tool versus siblings. The agent must infer usage from the purpose.
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?
No annotations are provided, so the description carries the full burden. It states the output fields, implying it is a read-only query with no side effects. However, it does not explicitly confirm safety, idempotency, or any required permissions.
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?
One sentence, front-loaded with the key purpose, and concise listing of output fields. No unnecessary words.
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?
For a tool with one parameter and no output schema, the description covers the return fields comprehensively. However, it omits parameter clarification, which would make it fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the single parameter 'name'. It adds no meaning beyond the schema's type definition. The agent cannot infer what value to provide for 'name'.
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 clearly states the action ('Full metadata') and the resource ('one namelist option'), listing specific output fields. It distinguishes from siblings like list_namelist_options (lists) and search_namelist_options (searches) by emphasizing 'full metadata' for a single option.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 such as list_namelist_options or search_namelist_options. The description does not specify when it is appropriate to retrieve full metadata versus a summary or search results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral transparency. It only mentions listing and optional filtering, lacking details about side effects, authentication needs, rate limits, or whether the operation is read-only. The description is insufficient for a no-annotation scenario.
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?
The description is a single, concise sentence that front-loads the action and key feature (optional filtering). No unnecessary words.
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?
With an output schema present, return values are covered, but the description lacks context about the scope of 'kVARS' (e.g., which model), pagination, or limits. It is adequate but incomplete for a list tool.
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?
Although the input schema has 0% description coverage, the description clarifies that the 'filter' parameter performs substring matching, adding meaning. However, it does not provide details on case sensitivity or format, so it only partially compensates.
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 clearly states the action (list) and the resource (kVARS model/output variables), and mentions optional substring filtering. This effectively distinguishes it from sibling tools like list_namelist_groups or search_model_variables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a use case (listing with optional filter) but provides no guidance on when to prefer this tool over alternatives like search_model_variables or get_model_variable. No exclusion criteria or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only says 'list' without disclosing any behavioral traits such as ordering, pagination, or output format. The existence of an output schema is not utilized in the description.
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?
The description is a single, short sentence with no wasted words, perfectly concise for the tool's simplicity.
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?
For a parameter-less list tool with an output schema, the description is minimally complete. However, it lacks context about what a 'documentation page' entails and how results are organized, which the output schema may not fully clarify.
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?
With zero parameters and 100% schema coverage, the description adds minimal meaning beyond the schema, but it correctly identifies the resource being listed. Baseline for 0 params is 4.
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 clearly states it lists HICAR documentation pages, using a specific verb and resource. It implicitly distinguishes from siblings like get_doc (single document) and search_docs (search versus list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 search_docs or semantic_search. No explicit when-not or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Full metadata' but does not specify what that includes (e.g., dimensions, attributes). There is a potential ambiguity: the description says 'by netCDF name or kVARS member' but the schema only has a single 'name' parameter, which may accept both. No mention of side effects, permissions, or whether the operation is read-only.
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?
The description is a single sentence that is concise and front-loaded with the primary purpose. Every word adds value with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and the complexity of returning metadata for a model variable, the description is insufficient. It does not describe the return value structure (e.g., dimensions, attributes, units). The parameter description is helpful but not exhaustive. Siblings like list_model_variables provide contrast but the tool's completeness is lacking.
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?
The schema provides only the parameter name 'Name' with no description. The tool's description adds significant meaning by clarifying that the parameter accepts a netCDF name or kVARS member. This compensates for the 0% schema description coverage, though it does not specify format constraints like case sensitivity or exact matching.
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 clearly states the tool retrieves full metadata for a model variable, specifying the identifier by netCDF name or kVARS member. This distinguishes it from siblings like list_model_variables (listing) and search_model_variables (search).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when full metadata for a specific variable is needed, but does not explicitly state when to use or not use this tool versus alternatives like list_model_variables or search_model_variables. No guidance on prerequisites or context is given.
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, the description carries the full burden. It implies read-only behavior (listing) but does not explicitly state it, nor does it disclose any side effects, permissions, or rate limits. The mention of output fields provides some transparency, but lacks a clear behavioral statement.
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?
The description is a single, well-structured sentence that front-loads the action ('List selectable schemes...') and efficiently conveys the key points without any unnecessary words.
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's simplicity (one parameter, output schema present), the description is mostly complete. It outlines the output contents and the role of the category. However, it could briefly mention that the category comes from list_physics_categories to fully contextualize the input.
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 description coverage is 0%, so the description must compensate. It clarifies that 'category' can be a category name or a selector like 'mp', and that it determines which schemes are listed. However, it does not explain the allowed values, format, or how it relates to list_physics_categories, leaving room for ambiguity.
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 clearly states the tool lists selectable schemes for a given category, specifying the output includes codes, originating constants, and supported status. It distinguishes from sibling tools like list_physics_categories (which lists categories) and resolve_physics_scheme (which resolves a specific scheme).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only explains what the tool does, not when to use it or alternatives. It offers no guidance on prerequisites, context, or trade-offs with sibling tools like resolve_physics_scheme or list_physics_categories. The agent is left to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only states it lists categories, with no mention of read-only behavior, side effects, or other behavioral aspects beyond the basic action.
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?
Single sentence, front-loaded with action and resource, with examples. No unnecessary words; every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (no parameters, simple list), the description sufficiently informs what the tool does. Output schema exists, so return values need not be described.
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?
No parameters exist in the input schema, so the description cannot add parameter semantics. Baseline of 4 applies since schema coverage is 100% and no parameters need explanation.
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 clearly states the action 'List' and the resource 'physics-scheme categories', with examples (microphysics, pbl, radiation). It distinguishes from sibling 'list_physics_schemes' which lists schemes, not categories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 'list_physics_schemes' or other listing tools. The description only states what it does, not the context or 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.
Behavior3/5
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 the two reading modes and the repository requirement, but does not address behavior with missing inputs, error handling, or whether operations are read-only.
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?
The description consists of two sentences with no redundant information. It front-loads the core purpose and concisely adds a critical requirement.
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 should provide more context about return format, error scenarios, and when to prefer this tool over siblings. The current coverage is adequate but not thorough.
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 description coverage is 0%, but the description adds context by explaining that path should be repo-rooted and start/end define a line range. However, it does not detail the meaning of 'symbol' or clarify the relationship between parameters.
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 clearly states the verb 'read', the resource 'HICAR source', and specifies two modes: by file path with line range or by symbol name. This differentiates it from sibling tools like code_search or get_doc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions a prerequisite ('Requires HICAR_REPO (live mode)') but does not explicitly state when to use this tool versus alternatives, nor 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description must fully disclose behavior. Only states search fields, but misses details like case sensitivity, partial matching, ranking, result limits, or pagination. Minimal disclosure for a search tool.
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?
Single sentence, no wasted words, front-loaded with action and resource. Highly concise.
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 the tool is a search with one parameter and has an output schema, the description is minimally adequate. However, lacks usage guidance and behavioral details that would help differentiate from many sibling tools. Could be more complete.
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 coverage is 0%, so description adds value by specifying that 'query' searches across name, standard_name, and description. This meaning is not in the schema. Could be improved by mentioning format (e.g., substring, regex) but still good.
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?
Clearly states verb 'Search' and resource 'model variables', specifying three searchable fields (name/standard_name/description). Distinguishes from siblings like 'get_model_variable' (single) and 'list_model_variables' (list all).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for text-based search of model variables, but no explicit guidance on when to use versus alternatives (e.g., 'semantic_search', 'code_search'). No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states the tool returns option counts, but does not mention whether it is read-only, requires authentication, or has any side effects. For a simple list operation, this is minimal but insufficient for full transparency.
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?
The description is a single sentence with no wasted words. It is front-loaded with the action and resource, and the output detail ('with option counts') is appended succinctly.
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?
For a zero-parameter list tool with an output schema, the description is reasonably complete. It doesn't elaborate on return format, but the output schema likely covers that. Given the tool's simplicity and the presence of output schema, no additional context is critically missing.
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?
There are zero parameters, so the baseline is 4 as per rule. The description adds value by clarifying that the output includes option counts, which is semantic meaning beyond the empty schema.
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 clearly states the verb 'List' and the resource 'HICAR namelist groups (&blocks)', and adds 'with option counts' to specify the output scope. This distinguishes it from siblings like 'list_namelist_options' which likely lists individual options, not groups.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. With many sibling tools such as 'list_namelist_options' and 'list_model_variables', the description does not clarify the context or exclusions. The tool has no parameters, so usage is straightforward, but the lack of differentiation is a gap.
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, the description carries full disclosure burden. It clearly states what information is reported but does not explicitly mention read-only nature, lack of side effects, or response format. The description is adequate but could add safety confirmation.
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?
The description is a single, well-formed sentence that front-loads the action ('Report') and succinctly lists all reported items. Every word earns its place with no redundancy or filler.
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 no parameters and no output schema, the description provides sufficient context for an agent to understand what it returns. It could marginally benefit from stating the output format (e.g., JSON), but it is largely complete for its simplicity.
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?
The tool has zero parameters, and schema coverage is 100% (trivially). No parameter explanation is needed; the baseline score of 4 applies as the description does not need to add anything beyond what's already empty.
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 specific verb 'Report' and lists exact pieces of information: server mode, discovered paths, version, and optional features. This clearly distinguishes it from sibling tools that focus on code search, namelist management, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention typical use cases, prerequisites, or exclusions, leaving the agent to infer from the tool name alone.
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?
Discloses the environmental dependency and mode behavior. As a search tool, it is implicitly read-only, and no annotations are provided. The description adds context beyond the schema.
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?
Extremely concise, front-loading the purpose in the first sentence and adding the dependency in the second. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite three parameters, the description lacks details on return format, pagination, regex behavior, and what fields are searched. For a search tool, more completeness is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate but does not explain individual parameters (query, regex, max_results). It only implies query is the search term, leaving agents to infer the rest.
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?
Description clearly states it performs lexical search over HICAR source (.F90 files) and documentation, differentiating it from sibling tools like semantic_search which probably do semantic search.
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?
Explicitly mentions the dependency on HICAR_REPO environment variable for source searches and the fallback to docs-only in bundled mode, giving clear guidance on when it works and under what conditions.
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?
No annotations are provided, so the description carries the full burden. It discloses that the tool parses, annotates each option, and flags validation issues. This is sufficient for a simple parsing tool; no hidden destructive behavior is expected.
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?
The description is a single sentence that covers the core functionality without any fluff. Every word adds value.
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 one parameter and no output schema, the description explains both input and output clearly. It could mention the expected format of the content (e.g., Fortran namelist), but the tool name and context make it understandable.
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?
With 0% schema coverage, the description adds meaning: the single 'content' parameter is a namelist to parse. It tells the agent what the parameter represents, compensating for the lack of schema descriptions.
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 clearly states the action (parse and annotate) and the output (descriptions, types, defaults, allowed values, validation issues). It distinguishes from siblings like validate_namelist (which only validates) and get_namelist_option (which gets a single option).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. However, from context and sibling tools, it is implied that this tool is for understanding a namelist's options in detail. No alternatives are mentioned.
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?
With no annotations, the description carries full burden. It discloses that static checks always run and binary checks are conditional on use_binary and HICAR availability. It does not specify output format or side effects, but as a validation tool, it is inherently safe and non-mutating.
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?
The description is two sentences, front-loaded with purpose, and each sentence adds value. No redundant information.
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 no output schema and no annotations, the description covers the tool's behavior and conditions. It could detail return values or error handling, but the conditional binary check and static checks are adequately described for a validation tool.
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 0%, so description must compensate. It explains that 'content' is a namelist string and 'use_binary' triggers a binary check if available. However, it does not define 'namelist' or expected format, leaving some ambiguity.
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 clearly states the tool validates a namelist string, detailing specific static checks (unknown groups/options, bad enum values, etc.) and a conditional binary check. This distinct verb-resource pairing differentiates it from sibling tools focused on searching, explaining, or generating namelists.
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?
The description implies the tool should be used to validate namelist strings, and sibling names make the distinction clear. However, it lacks explicit guidance on when not to use or alternatives, and the conditional nature of the binary check is mentioned but not fully elaborated.
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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