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

The description discloses that the tool writes markdown files and can overwrite them via force_overwrite. This aligns with annotations (non-read-only, non-destructive, but overwrite is noted). No contradiction.

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 relatively long with code blocks and redundant parameter listings. It could be more concise by omitting the duplicate parameter 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?

Given the complexity (7 parameters, nested object), the description covers the main functionality, parameters, return, and usage examples. It does not explain the output schema but that is not required. It is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes all parameters, and the description's 'Args' section largely duplicates that information without adding significant new meaning. The descriptions are similar, so minimal added value.

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 generates catalog controls in markdown form, with a specific verb and resource. Sibling tools are all different (profile operations, import, init), so no confusion.

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 includes explicit 'Use when' and 'Don't use when' examples, providing clear usage contexts. However, it does not directly reference sibling tools as alternatives, so it is not perfect.

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 indicate readOnlyHint=false (writes), destructiveHint=false (non-destructive), and idempotentHint=false. The description adds that the tool writes a profile.json file and returns a success/error string. While it doesn't detail permissions or exact side effects, it aligns with annotations and provides basic behavioral context. The openWorldHint=true suggests no external dependencies are hidden, but the description lacks explicit statements about file system impact or required environment setup.

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 well-structured with headings (purpose, args, returns, examples) and bullet points, making it easy to scan. It front-loads the core purpose. However, it is somewhat verbose; the 'Args' section could be more concise since the schema already describes parameters. The examples are helpful but repeated phrases ('Use when') could be trimmed. Overall, it is efficient for a complex tool with many parameters.

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 covers the tool's purpose, all parameters with descriptions, return value, and usage examples including contraindications. It does not explain the output file structure (e.g., profile.json contents) beyond being a JSON, but the output schema is marked as present. Given the complexity (1 complex param with many sub-params), the description is complete enough for an agent to invoke correctly. Missing details like required trestle root setup or dependency on trestle_init are minor gaps.

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?

Although context signals report 0% schema description coverage (likely due to the top-level 'params' object lacking a description), the provided schema includes descriptions for each sub-property in the $defs. The description's 'Args' section reiterates all parameters with concise explanations and includes formatting hints (e.g., comma-separated for sections). This adds meaning beyond the schema, especially for optional parameters with defaults (e.g., set_parameters, regenerate). A slight deduction for not explaining the meaning of 'sections' in more detail.

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 assembles markdown controls into an OSCAL Profile JSON file. It specifies the verb 'assemble' and the resource 'Profile JSON from Markdown Directory', distinguishing it from siblings like profile_generate (which likely generates markdown from profile) and profile_resolve (which resolves profiles). The title and first sentence are unambiguous.

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 includes explicit 'Use when' and 'Don't use when' examples, providing clear guidance on appropriate contexts (e.g., CI/CD assembly, parameter expansion) and contraindications (missing or malformed markdown). However, it does not directly compare to sibling tools like trestle_author_profile_generate or trestle_author_profile_resolve, which would further clarify when to choose this tool over alternatives.

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?

Discloses file generation behavior and overwrite options, complementing annotations. Annotations already indicate non-read-only and open-world behavior, and the description adds context about creation and overwriting.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is front-loaded with purpose, followed by structured parameter list and examples. Slightly verbose but well-organized and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers input, output (returns string), and usage examples. Lacks some details on default behaviors and output format, but adequate given the output schema exists.

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?

Though the schema provides descriptions for each property (0% top-level coverage), the tool description lists and explains each parameter, adding clarity on their roles and defaults.

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 'Generate markdown documentation set for controls defined in specified profile' with specific verb and resource. It distinguishes from siblings like trestle_author_catalog_generate by focusing on profile controls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit use cases ('Use when: ...') and a negative case ('Don't use when: Profile file does not exist'). However, it does not differentiate from sibling tools like trestle_author_catalog_generate.

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 explains the resolution process (resolves to a catalog), mentions output formatting options, and specifies the file path convention ('profiles/<name>/profile.json'). The return type and error behavior are described. Annotations indicate no destructiveness or idempotency, which is consistent. Some behavioral details like file creation are implied but not explicit.

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 well-structured with a clear purpose statement, a detailed parameter list, and an examples section. It is front-loaded with the main action, but the parameter list is somewhat lengthy and could be more concise without losing clarity.

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 covers the main purpose, parameters, return value, and an example. It mentions the file path convention and optional parameters. However, it does not explain prerequisites (e.g., existence of the profile) or the effect of 'trestle_root', leaving some gaps for a complete context.

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 has detailed descriptions for each parameter, and the tool description repeats this information in the Args section with added context like default values and examples. However, the repetition does not significantly add meaning beyond the schema, resulting in a baseline score of 3.

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 'resolve' and the resource 'OSCAL profile to catalog', matching the title. It specifies the operation and distinguishes from sibling tools like 'trestle_author_profile_generate' or 'trestle_author_profile_assemble'.

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 guidance on when to use this tool over alternatives. No comparisons or explicit conditions are given, leaving the agent to infer context 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.

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

Annotations are sparse but the description adds significant behavioral context: file saving paths per OSCAL type, argument details, and return type. No contradiction with annotations. Describes the import process well.

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 well-structured with sections, front-loaded purpose, and examples. It is somewhat lengthy but each sentence adds value. Could be slightly more concise.

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 tool's complexity (one compound parameter with five sub-parameters) and the presence of an output schema, the description covers input format, output, and examples. It is sufficiently complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% per context signal, so the description must compensate. It lists all parameters with brief explanations but does not add much beyond the schema's own descriptions. Adequate but not exceptional.

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 explicitly states 'Import an existing OSCAL model into the trestle workspace' and details the types of OSCAL models it handles. It distinguishes itself from sibling tools (generation, assembly, resolution, initialization, CSV conversion) by being the import tool.

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 clear guidance on when to use the tool (importing OSCAL models from URLs or local files) and includes examples. It does not explicitly state when not to use it or alternatives, but the sibling tool list implies the context.

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 indicate idempotent behavior, which the description does not contradict. The description adds context about creating directory structure and available modes, going beyond what annotations provide. No mention of side effects, but idempotent implies safety.

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?

Well-structured with a clear purpose, list of supported models, args section, returns, and examples. Front-loaded with main action, each sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Comprehensive for a initialization tool: covers purpose, modes, return type, and usage examples. Output schema reduces need for extensive return descriptions; the provided 'Success message or error details' 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?

The input schema already provides descriptions for all parameters (mode, trestle_root, verbose). The description adds no new parameter-level details beyond listing them generically, so it does not significantly improve understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'initialize' and the resource 'trestle working directory'. It lists supported OSCAL model types, distinguishing it from sibling tools like trestle_import or trestle_task_* 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Includes 'Use when' and 'Don't use when' examples, providing clear guidance on appropriate contexts. Does not explicitly mention sibling tools as alternatives, but the 'Don't use when workspace is already initialized' is helpful.

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 set readOnlyHint=false and destructiveHint=false, so no contradiction. Description explains it produces an output file and returns success/error message, but does not detail potential side effects or permissions beyond file creation.

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?

Well-structured with bullet points and examples, but could be slightly more concise. No redundant sentences.

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?

Comprehensively covers the tool's purpose, input requirements, output, and examples. With an output schema present, no need to describe return values in detail.

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 has detailed descriptions for each parameter, so the description adds moderate value by explaining the required CSV columns and overall workflow. Schema coverage is effectively high, so baseline applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool converts CSV to OSCAL component definition JSON. It specifies the command and the CSV format, distinguishing it from sibling trestle tools which handle catalog, profile, import, and init tasks.

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?

Includes explicit 'Use when' and 'Don't use when' examples, providing context for appropriate usage. Does not explicitly compare to sibling tools, but the task is specific enough.

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 provide no helpful behavior hints (all false), so the description carries the full burden. It discloses that the task produces a JSON file, auto-generates observations[] and risks[] with deterministic UUIDs, may overwrite existing output via output_overwrite, and requires a trestle workspace. It also explains the spreadsheet row layout and required columns, which are critical behavioral inputs. No contradiction with annotations is present.

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 long, but the tool is complex and every section earns its place: summary, workspace prerequisite, spreadsheet format, required columns, parameter list, return value, and concrete usage examples. It is front-loaded with the one-line purpose, and the structure makes it easy for an agent to extract the key constraints quickly.

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 conversion task with a complex input format, the description is complete: it covers the input file structure, required columns, workspace setup, output location semantics, validation behavior, and exclusion cases. The presence of an output schema slightly reduces the burden for return-value details, but the description still provides a Returns summary. An agent has everything needed to decide whether and how to invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does thoroughly. It enumerates every parameter with its type, default, and whether it is required, including nuanced ones like validate_required_fields ('on/warn/off') and work_sheet_name ('Open POA&M Items'). It also adds meaning to xlsx_file by describing the exact spreadsheet layout and required columns that the schema only briefly touches on.

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 opens with a precise verb+resource+result statement: 'Convert a FedRAMP XLSX spreadsheet to an OSCAL POA&M JSON file.' It names the exact input format, the output format, and the underlying command, making the tool's purpose unmistakable. The sibling-differentiating details are present through the explicit 'Don't use when: The input is a CSV' exclusion, which separates it from CSV-oriented sibling 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 gives explicit when-to-use examples ('Convert this FedRAMP POA&M spreadsheet to OSCAL') and when-not-to-use conditions ('Don't use when: The input is a CSV, or is missing required columns'). It also states the prerequisite: the command must run inside a trestle workspace initialized with trestle_init. This gives an agent clear decision criteria and environmental setup 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?

Read-only, idempotent, non-destructive annotations already establish safety. Beyond that, the description explains model-type auto-detection, optional semantic validators, and what happens on failure, which the annotations do not cover. It provides meaningful behavioral context without contradicting hints.

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 structured with a clear summary, an Args section, Returns, and Examples. The essential scope and primary usage are front-loaded, and the 'Don't use when' note appears at the end without bloating the start. Every sentence contributes distinct information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the rich input schema, output schema, and read-only annotations, the description covers the required inputs, an optional parameter, semantic validation behavior, accepted file formats, supported models, and non-workspace scope. Little is left for the agent to infer.

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?

Even though the schema's parameter descriptions are detailed and cover all three fields, the tool description adds value by restating the file path requirement, the default for semantic validation, expected_model_type example values, and the POA&M use case. The description does not fully duplicate the schema, and its examples clarify parameter selection.

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 begins with a specific verb and resource: 'Validate a standalone OSCAL file against the OSCAL schema.' It enumerates supported model types and explicitly contrasts itself with the CLI `trestle validate` on workspaces, giving it distinct identity among siblings.

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 gives explicit use cases and a 'Don't use when' condition, routing the agent away from the CLI workspace-based validation. Examples map concrete natural-language requests to parameter values, so when-to-use is unambiguous.

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