Server Quality Checklist

Tool Scores

• cleanroom_impl_run_testsA
  3.7/5.0
  Behavior3/5

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

  With no annotations provided, the description must disclose behavioral traits. It says the tool 'executes the test command in the implementation directory' and 'returns results,' but it does not detail the output format, potential side effects of running arbitrary commands, or any assumptions about the environment.

  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, with the core purpose front-loaded. Every sentence adds information, and there is no redundancy with the schema.

  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?

  The tool is simple (2 optional parameters, no output schema), and the description covers the essential action and location. However, it lacks details about how results are returned (format, exit codes) and does not mention the default test command, which is only in the schema. This leaves some ambiguity for the agent.

  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?

  Both parameters are fully described in the schema with 100% coverage, so the baseline is 3. The description adds a brief context about filtering by spec ('Optionally filter to tests for a specific spec') but does not elaborate on parameter syntax or behavior beyond the 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 tool's function: 'Run the test suite for the reimplementation.' It specifies the action (run) and resource (test suite), and uses 'implementation directory' to set context, distinguishing it from sibling verification tools like cleanroom_verify_run.

  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 testing the reimplementation but provides no explicit guidance on when to choose this tool over alternatives. Sibling tools like cleanroom_verify_run are not mentioned, and there are no exclusion criteria or prerequisites.

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

• cleanroom_spec_reviewA
  3.7/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It discloses the review criteria (only observable behavior, no implementation details) and the approve/reject outcomes. However, it does not mention side effects, permissions, or what happens after approval, leaving some ambiguity about state changes.

  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 the main action, and every word is meaningful. It avoids redundancy and is appropriately sized for the tool's complexity.

  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?

  The description covers the core workflow but does not explain return values or the exact state transition after approval/rejection. Given the lack of an output schema and annotations, this is a noticeable gap. The tool has 4 parameters and no output schema, so more context would be helpful, but the description is not severely incomplete.

  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 75%, and the description reinforces the purpose of feedback ('which sections need revision') but does not add significant detail beyond the schema. The schema already defines the parameters and their constraints, so the description adds marginal value. Baseline of 3 is appropriate.

  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's function: reviewing a submitted specification for contamination. It specifies the verb 'review' and the resource 'specification', and distinguishes itself from siblings by focusing on contamination checking and approve/reject decisions.

  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 context (after submission, for handoff approval) but does not explicitly mention alternatives or exclusions. It says 'Approve it for handoff or reject it with specific feedback', which gives some context, but lacks direct comparison to sibling tools. This is borderline but not as specific as a dedicated usage guideline.

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

• cleanroom_audit_exportA
  3.8/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It discloses that the export includes all entries with hash chain, timestamps, and actor information, which is useful. However, it does not mention side effects like creating files via output_path, potential large data handling, or performance implications, leaving some behavioral aspects opaque.

  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, immediately states the tool's action and purpose, and avoids redundancy. Every sentence adds value: the first defines the action and format, the second elaborates on content included in the export.

  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 3 optional parameters and no output schema, the description covers the core purpose, formats, and content. It could be enhanced by mentioning the file-writing behavior or return value, but the schema parameter ('Path to write the export file') partially covers that. The tool is relatively simple, and the description is mostly complete for a compliance export.

  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 schema already covers 2 of 3 parameters with descriptions, and the description adds context that the export is 'complete' and includes hash chain, which indirectly relates to include_details. However, it does not clarify the format enum semantics beyond what the schema provides, and the output_path default is not explained in the description. Overall, it does not significantly exceed schema value.

  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 exports the complete audit trail in JSON or CSV format for compliance and legal documentation. It uses a specific verb ('export'), names the resource ('audit trail'), and specifies formats, distinguishing it from sibling tools like cleanroom_audit_log (likely logs events) and cleanroom_audit_verify (likely verifies integrity).

  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 compliance records and legal documentation, but does not explicitly state when to use this over alternatives like cleanroom_audit_log or cleanroom_audit_verify, nor does it provide exclusions or prerequisites. It offers a clear purpose but lacks explicit 'when not to use' guidance.

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

• cleanroom_verify_reportA
  3.8/5.0
  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 discloses the output content and the two reporting modes, but does not explicitly state that it is read-only, requires prior verification runs, or how it handles missing data. This leaves some ambiguity for a report generator.

  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 the verb 'Generate,' and contains no redundant information. Every word adds value, making it concise and well-structured.

  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 tool with a single optional parameter and no output schema, the description covers the core behavior and output contents. However, it omits the format parameter and any edge-case behavior (e.g., no runs exist), leaving some gaps for an agent to infer.

  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?

  The description does not mention the 'format' parameter at all, despite schema description coverage being 0%. The enum values (summary, detailed, json) are somewhat self-explanatory, but the description does not clarify how they affect the report or relate to the two modes mentioned in the description, creating potential confusion.

  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 generates a report from the most recent verification run or a summary of all runs, listing specific contents (match rates, mismatched cases, spec coverage). It distinguishes itself from sibling tools like cleanroom_verify_run, which executes verification, by focusing on reporting.

  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 usage after verification runs and clearly contrasts two modes (recent run vs. all runs). It does not explicitly exclude alternatives or name when not to use it, but the context is clear.

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

• cleanroom_ai_logA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It does state that the tool writes to an audit trail and lists the kinds of data it records, but it does not mention potential side effects, permission requirements, whether the operation is append-only, or what the response contains. This is adequate but not rich.

  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 long, front-loaded with the core purpose ('Log AI agent activity to the audit trail'), and contains no redundant information. It earns its place with every word.

  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 moderate complexity (5 parameters, no output schema, no annotations), the description is reasonably complete. It explains what the tool does, when to use it, and what data it logs. It does not describe return values, but for a logging tool this is a minor omission. It could also mention any prerequisite cleanroom context, but overall it suffices.

  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 100%, so the parameters are already well-documented. The description adds minor semantic context by mentioning 'session starts' (relating to session_id) and 'context that was provided to the agent' (context_provided), but these largely mirror the schema descriptions. It does not significantly enhance beyond the 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 tool's function: 'Log AI agent activity to the audit trail.' This uses a specific verb ('log') and resource ('AI agent activity' to 'audit trail'), and it distinguishes itself from siblings such as cleanroom_audit_log by focusing specifically on AI agent actions.

  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 provides clear usage guidance: 'Call this to record significant actions taken by AI agents, including session starts, model identifiers, and context that was provided to the agent.' This establishes when to use the tool but does not explicitly mention when not to use it or offer alternatives among siblings, so it stops short of a full 5.

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

• cleanroom_audit_logA
  4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the disclosure burden. It adds useful behavioral context beyond the schema, including that the audit trail is tamper-evident, hash-chained, and logs every tool call, spec handoff, review decision, access denial, and attestation with timestamps. This reveals the read-only, comprehensive nature of the operation, though it does not detail pagination or response format.

  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 long, front-loaded with the primary purpose, and every sentence adds value. The first sentence states the main function; the second elaborates on the content and capabilities without redundancy.

  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 (no output schema, simple parameters, read-only nature), the description is complete enough for an agent to select and invoke it. It explains what is logged, the tamper-evidence aspect, and filtering options. It could mention default limit behavior or return format, but these are not critical for this kind of 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?

  The schema covers 67% of the parameters (limit and since have descriptions, filter_type has an enum). The description adds context about filtering by type and date, which maps to filter_type and since, but does not mention the 'limit' parameter. This is a minor gap, but the description provides meaningful context beyond the schema's bare parameter 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's purpose: to view the project's tamper-evident audit trail. It specifies the resource (audit trail) and action (view), and distinguishes it from sibling tools like cleanroom_audit_verify and cleanroom_audit_export, which are for verification and export rather than viewing.

  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 explains what the tool does and that it supports filtering by type and date, giving a clear context for when to use it (to view audit logs). However, it does not explicitly state when to use it over sibling tools like cleanroom_audit_verify or cleanroom_audit_export, nor does it mention exclusions or prerequisites.

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

• cleanroom_initA
  4/5.0
  Behavior3/5

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

  Since no annotations are provided, the description carries the full burden. It discloses the main actions: creating directories, config file, and audit trail. However, it does not address edge cases like whether re-running the tool is safe, what happens if the project already exists, or any destructive potential. This is adequate but lacks detail on side effects or error behavior.

  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, directly front-loaded with the core action and then adding relevant detail about what is set up and when to use it. Every sentence earns its place with no filler or redundancy, ideal for quick comprehension.

  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 simple initialization tool with no output schema, the description explains what it creates, when to use it, and implies the workflow. It does not cover what the function returns or what happens on error/duplicate project, but given the sibling tools for audit and status, the context is fairly complete. Slightly above average due to clear purpose and usage.

  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 input schema covers all 5 parameters with descriptions, so the baseline is 3. The tool description does not add any parameter-specific details beyond what the schema already provides. It mentions 'standard directory structure' and 'proper separation,' which are project-level behaviors but not tied to individual 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 tool's purpose with a specific verb ('Create') and resource ('new clean-room reimplementation project'). It distinguishes itself from siblings by focusing on initialization, explicitly naming the directory structure and audit trail setup, and concluding with the use case 'at the start of a new clean-room project.'

  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 provides explicit usage timing with 'Use this at the start of a new clean-room project,' which is clear contextual guidance. It does not name alternative tools or explicitly state when not to use, but the initialization focus implicitly excludes later stages. This is slightly above average due to the explicit 'when,' though it lacks formal exclusions or alternatives.

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

• cleanroom_spec_createA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the transparency burden. It adds useful behavioral details: the spec starts in 'draft' status and the tool enforces documentation of 'observable behavior without including implementation details.' However, it doesn't mention permission requirements, behavior on duplicate names, or what the tool returns after creation, leaving some ambiguity for a mutation 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?

  The description is three sentences with no filler: it states the core action, the structured template approach, the resulting draft status, and lists the available templates. Every sentence contributes necessary information, and the structure is efficient and easy to scan.

  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?

  The description covers the tool's purpose, the template options, the constraint on content, and the initial status, which is sufficient for an analyst to decide to use it. There is no output schema and no mention of return values or next steps, but the create action is straightforward and the missing details are not critical for this tool's usage.

  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 input schema provides 100% coverage of the four parameters with descriptions, including the enum for template and the constraint on initial_content. The description repeats the template list but adds no significant new parameter-level meaning beyond the schema. Baseline 3 applies since the schema already documents everything.

  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's function: 'Create a new behavioral specification for a component of the target software.' The verb 'create' plus the resource 'behavioral specification' distinguishes it from sibling tools like cleanroom_spec_read, cleanroom_spec_list, and cleanroom_spec_submit, which handle other lifecycle stages.

  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 provides context about when to use the tool: to create a new spec in 'draft' status using a structured template. It doesn't explicitly mention alternatives or when not to use, but the sibling tool names (e.g., cleanroom_spec_submit, cleanroom_spec_review) imply these are for later stages, making the create tool's role clear.

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

• cleanroom_spec_listA
  4/5.0
  Behavior4/5

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

  Without annotations, the description discloses a key behavioral trait: role-based visibility where implementers only see handed-off specs. It also states the summary fields returned, adding transparency 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?

  Three sentences, front-loaded with purpose, and no redundant information. Every sentence adds value: purpose, filtering, role-based visibility, and return summary.

  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 with an enum and no output schema, the description covers the key aspects: filtering, role behavior, and return fields. Slight gap is lack of pagination or ordering details, but it is quite complete 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?

  Schema coverage is 100%, and the description mentions filtering by status but does not add meaning beyond the schema's enum description. Baseline 3 is appropriate as the schema fully documents the parameter.

  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 all specifications in the project, with a specific verb ('list') and resource ('specifications'). It also distinguishes from siblings like cleanroom_spec_read (single spec) and cleanroom_team_list (teams).

  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?

  Provides context on filtering by status and notes implementers see only handed-off specs, but does not explicitly state when to use this versus alternatives or give exclusions. The guidance is implied rather than direct.

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

• cleanroom_spec_readA
  4/5.0
  Behavior4/5

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

  With no annotations, the description carries the burden. It discloses the permission model and implies read-only behavior. This is meaningful context beyond the tool name, though it omits details about output format or side effects (though side effects are not expected for a read operation).

  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 concise, with three sentences that front-load the purpose and then efficiently detail access rules. Every sentence contributes value with no redundancy.

  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 simple read tool with one parameter and no output schema, the description covers the essential context, especially the role-based access policy. It does not describe the return format, but that is not critical for such a straightforward operation.

  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 input schema already has 100% description coverage for the single 'name' parameter ('Spec name to read'). The description adds little beyond the generic phrase 'contents of a specification', so it does not significantly enhance parameter understanding.

  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 'Read the contents of a specification' with a specific verb and resource. It adds role-based scope, but does not explicitly differentiate from the sibling tool cleanroom_impl_read_spec, which may also read specs.

  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?

  Provides clear context on who can read what (analysts, implementers, monitors), including the permission constraint for implementers. However, it does not name alternatives like cleanroom_impl_read_spec or state when to use one over the other.

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

• cleanroom_team_listA
  4/5.0
  Behavior3/5

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

  No annotations exist, so the description must carry the full burden. It indicates a read operation via 'List all team members' and specifies the returned fields (roles, types, metadata). However, it does not mention authorization requirements, ordering, or edge-case behavior such as empty project states.

  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, front-loaded sentence that conveys the essential scope and included metadata with no redundant content.

  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 parameterless list tool with no output schema, the description covers what is returned (roles, types, metadata) and the scope. It could potentially mention edge cases, but this is sufficient for the complexity level.

  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 the schema is empty, so there is nothing to explain. The baseline score of 4 applies.

  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 states 'List all team members in the clean-room project with their roles, types (human/AI), and any associated metadata.' This clearly identifies the action (list), resource (team members), and scope (clean-room project), and distinguishes from sibling tools like cleanroom_team_add.

  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 viewing team composition but does not explicitly state when to use this tool versus alternatives such as cleanroom_status or cleanroom_team_add. No exclusions or alternative guidance is provided.

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

• cleanroom_attestA
  4.1/5.0
  Behavior4/5

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

  No annotations are provided, so the description must disclose behavioral traits itself. It states that 'Attestations are permanently recorded in the audit trail,' which warns the agent that the operation is non-reversible and persistent. It stops short of mentioning authorization or side effects beyond the audit trail, but covers the core write behavior.

  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 three sentences: purpose, two-mode breakdown, and permanence. Every sentence adds distinct value with no redundant phrasing.

  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?

  With six parameters and no output schema, the description covers the essential usage context (human vs AI, statement expectations, audit permanence) and works alongside the schema's enums. It lacks explicit prerequisites (e.g., cleanroom must be initialized) or interaction notes with sibling logging tools, but is adequate for the tool's complexity.

  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 67%, and the description adds context beyond the schema by explaining that for humans the statement confirms non-access and for AI it discloses training data/access scope. This maps directly to the 'statement' and 'training_data_note' parameters and clarifies the two attestation_type values. It doesn't describe the role enum, but the enum values are self-explanatory.

  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 uses a specific verb ('Record') and resource ('attestation for the clean-room process'), and clearly separates human vs AI use cases. It does not explicitly mention sibling tools or alternatives, so it doesn't fully distinguish from overlap like cleanroom_ai_log, but the purpose is unambiguous.

  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 provides clear context: use for human team members to confirm non-access, and for AI agents to record data access and training disclosures. It does not name when not to use it or compare to alternative tools, but the guidance is concrete enough to decide when to invoke.

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

• cleanroom_spec_submitA
  4.2/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the burden. It discloses what happens after submission (the monitor checks for contamination) and the state restriction (only draft/rejected). This gives useful behavioral context beyond the schema, though it does not specify return values or failure modes.

  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, immediately front-loaded with the verb and object. Every phrase contributes meaningful context without redundancy. It is concise and well-structured.

  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 simple submission action with only 2 parameters and no output schema, the description covers purpose, constraints, and the review process. It does not explicitly describe the post-submission status or response, but for this tool's simplicity, the information is sufficient.

  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 100% (both 'name' and 'notes' are described in the schema). The description adds no additional parameter-level detail beyond what the schema already provides. Baseline 3 is appropriate because the schema does the heavy lifting.

  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 specific action ('Submit a draft specification for contamination review') and identifies the resource ('draft specification') and the reviewer ('the monitor'). It distinguishes this tool from siblings like cleanroom_spec_review (which performs the review) and cleanroom_spec_create (which creates the spec).

  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?

  It states a clear precondition: 'Only draft or rejected specs can be submitted.' This tells the agent when the tool is applicable. It does not explicitly name alternatives, but the constraint implicitly excludes other spec states. The context is sufficient for selection.

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

• cleanroom_statusA
  4.2/5.0
  Behavior4/5

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

  Since no annotations are provided, the description carries the burden. It clearly signals this is a non-destructive read operation via 'Get' and 'Shows', and discloses the informational scope (spec statuses, team, audit integrity). It does not mention any side effects or permissions, but for a read-only status tool these are not critical.

  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-loads the main purpose, and every clause adds specific information. No fluff.

  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?

  With no output schema, the description does a good job summarizing the return content: spec progress, team composition, audit chain status. It could be more detailed about formatting or exact outputs, but it's sufficient for an overview tool.

  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, so there is nothing to explain. The description adds value by describing what the status report contains, but since no parameters exist, the schema fully covers this aspect. 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 uses the verb 'Get' to specify a read operation and clearly identifies the resource: 'current status of the clean-room project'. It enumerates three specific aspects (spec progress, team members, audit trail integrity) which distinguishes it from sibling tools like cleanroom_spec_list or cleanroom_team_list that focus on individual components.

  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 this is the tool for an overall status overview ('summary of all specifications...'), but it does not explicitly state when to use it over alternatives or mention any exclusions. It provides clear context but no direct comparison with sibling tools.

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

• cleanroom_impl_read_specA
  4.3/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the burden of behavioral disclosure. It reveals that the tool returns full spec content and extracted acceptance criteria, and that access is restricted to handed-off specs. This is useful, though it stops short of describing error behavior or permission requirements.

  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 concise, using two sentences to convey purpose, return value, and access restriction. It is front-loaded with the key verb and resource, and every phrase adds value.

  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 tool's simplicity (one parameter, no output schema, read-only nature), the description is complete. It explains what the tool does, what it returns, and the condition for use—all essential information for an agent to select and invoke it correctly.

  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 input schema already provides full coverage for the single 'name' parameter, including the 'must be handed-off' constraint. The description adds no significant new semantics beyond what the schema states, so a baseline score of 3 is appropriate.

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

  Purpose5/5

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

  The description clearly identifies the tool's purpose: reading a specification that has been handed off to the implementation team. It distinguishes this from the sibling cleanroom_spec_read by emphasizing the 'handed-off' scope and by noting it returns acceptance criteria alongside the full spec content.

  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 explicitly states that only handed-off specs are accessible, which gives clear context on when this tool applies. However, it doesn't explicitly name alternative tools (e.g., cleanroom_spec_read) or state when not to use this tool, so it lacks full exclusion guidance.

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

• cleanroom_verify_runA
  4.3/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly discloses the black-box nature, treats both executables as opaque, and details the comparison modes. However, it does not describe the return value or status semantics, which is a gap given the lack of an output 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?

  The description is four sentences long, front-loaded with the main purpose, and every sentence adds distinct value. It avoids repetition of schema details and is well-structured for quick parsing.

  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?

  The tool has 5 parameters and a nested test_cases structure, with no output schema or annotations. The description covers mechanism and constraints but omits what the tool returns after comparison (e.g., pass/fail per test case, exit codes, or a report reference), which is essential for an agent to act on results. This is a notable gap.

  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 description coverage is 80%, so the baseline is 3. The description adds value by explaining the comparison_mode enum values in detail (exact, fuzzy, semantic) and clarifying that test_cases are fed identically to both commands, which goes beyond the schema's minimal 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 compares the reimplementation's behavior against the original software using black-box testing, specifying the verb and resources. It also distinguishes this from sibling tools like cleanroom_verify_report, which likely handles reporting, and cleanroom_impl_run_tests, which likely runs tests.

  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 provides clear context on execution method (feeds identical inputs, compares outputs, no source code access), making it obvious when this tool is appropriate for behavioral verification. It does not explicitly name alternative tools or exclusions beyond stating it does not access source code, so it misses the full 'when-not' guidance.

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

• cleanroom_audit_verifyA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly explains the mechanism (SHA-256 hash chain), what it detects (modified, added, or removed entries), and the outcome ('detect the break point'). It also states the access policy ('All roles can verify'). This is strong transparency for a read-only verification tool, though it does not explicitly state whether it returns a simple pass/fail or detailed report.

  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 extremely concise: two sentences, front-loaded with the verb and resource, and each sentence adds meaningful information. There is no fluff or repetition of the title/name.

  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 simple, no-parameter tool with no output schema, the description covers what it does, how it works, and who can use it. It might be slightly more complete if it mentioned the return format or edge cases, but given the tool's simplicity, the description is adequately 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?

  The tool has zero parameters, and the schema shows no properties. Per the scoring rules, a baseline of 4 is appropriate when no parameters exist. The description adds no parameter-level detail because none is needed; the schema already has 100% coverage.

  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 a specific verb 'Verify' with a clear resource ('audit trail') and method ('checking the SHA-256 hash chain'). It clearly distinguishes itself from sibling tools like cleanroom_audit_log and cleanroom_audit_export, making its purpose unambiguous.

  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 statement 'All roles can verify the audit trail' provides clear context about when the tool can be used, implying it is appropriate for any user without special permissions. It does not explicitly mention alternatives, but for a verification tool with no parameters, the context is sufficient to infer its role relative to siblings.

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

• cleanroom_team_addA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses a key behavioral constraint: 'Only the lead role can add team members,' and explains the consequence of role assignment: 'Each member is assigned a role that determines their tool access.' This adds context beyond the schema's enum values about the significance of the role parameter, though it does not describe the exact return value or failure behavior.

  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 extremely concise, consisting of two sentences that convey the purpose, the accepted member types, the role's significance, and the permission constraint. It is front-loaded with the action and contains zero redundant or filler language. Every sentence contributes essential 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 the tool's complexity (5 parameters, 3 required) and the absence of an output schema and annotations, the description covers the core semantics adequately: what it does, what role behavior is, and who can invoke it. It lacks explicit mention of failure modes or the result of a successful add, but for a straightforward 'add' operation with a clear schema, this is a reasonable level of completeness.

  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 100%, so the baseline is 3. The description adds value by explaining that the 'role' parameter determines tool access, which provides meaning beyond the schema's simple 'Role assignment' description. It also clarifies that 'type' can be human or AI, reinforcing the schema. This contextual enrichment justifies a score above baseline.

  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's action: 'Add a team member (human or AI agent) to the clean-room project.' It specifies the verb ('add'), the resource ('team member'), and the context ('clean-room project'), and distinguishes it from sibling tools like cleanroom_team_list or cleanroom_init by being the team member creation operation. It also clarifies the types of members (human or AI) and the role-based access system.

  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 provides a clear usage condition: 'Only the lead role can add team members,' which tells the agent when this tool is applicable and the prerequisite role. While it does not explicitly name alternative tools, the inclusion of the role restriction effectively guides when to attempt the operation. The purpose is specific enough that usage versus listing or other operations is understood.

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

• cleanroom_spec_handoffA
  4.5/5.0
  Behavior5/5

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

  With no annotations, the description carries full responsibility. It explicitly discloses the irreversible nature ('IRREVERSIBLE', 'cannot be modified'), the copy action, resource availability, and audit record creation. This goes beyond a simple verb+object and provides critical behavioral expectations.

  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, efficient and front-loaded with the core purpose, followed by important caveats. No word is wasted.

  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?

  Despite having no output schema and only one parameter, the description provides a complete picture: the trigger (approved spec), the actions (copy, resource, audit), and the constraint (irreversibility). This is sufficient for an agent to invoke it correctly.

  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 schema already fully documents the single 'name' parameter with its own description. The tool description does not add any additional semantics beyond what is in the schema, such as validation rules or format, so it meets the baseline but adds no extra value.

  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's purpose: 'Release an approved specification to the implementation team.' It goes beyond the title by detailing the actions (copies to handoff directory, makes available as MCP Resource, creates audit record) and distinguishes it from sibling tools like review or submit by indicating this is the final handoff step.

  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 provides clear context: it must be used for an 'approved specification,' implying it follows the review step. However, it does not explicitly state when not to use it or name alternative tools, so it stops short of full exclusion guidance.

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