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

No annotations provided; description only says 'adds a relationship' without disclosing mutation effects, prerequisites, or error states. Does not explain behavior on duplicate links or 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.

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

Two concise sentences: first defines action, second provides context. No redundant or filler content.

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

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

With 8 parameters and no output schema, the description lacks guidance on parameter selection (e.g., when to use each relationship type) and does not mention return value or validation outcomes.

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

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

Schema coverage is 100% with detailed parameter descriptions. The description adds no extra meaning beyond 'directed or bidirectional' which maps to the bidirectional field. Baseline 3 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?

Clearly states verb 'Add' and resource 'causal relationship between Why nodes'. Distinguishes from linear 5-Why chain, providing specific use cases (escalation loops, feedback cycles, mitigation links).

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?

Explicitly states when to use (non-linear relationships). Implicitly differentiates from rc_add_cause but lacks explicit 'when not to use' or alternative references.

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?

No annotations are provided, so the description carries the full burden. It fails to disclose side effects (e.g., whether it modifies the session state), return behavior, error conditions, or dependencies. The description only repeats information already available in the parameter schema without adding 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.

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

The description is a single, efficient sentence that front-loads the primary action. It is not verbose, and every word serves a purpose. However, it could benefit from a brief structured layout for clarity, such as separating the primary action from optional 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 6 parameters, no output schema, and no annotations, the description is too sparse. It omits crucial context such as the need for a prior session, error handling, and the meaning of HFACS classification. A more complete description would explain typical usage and expected outcomes.

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

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

Schema description coverage is 100%, granting a baseline of 3. The description adds minimal meaning beyond the schema: it mentions sub-causes, evidence, and HFACS classification, which are already defined as optional parameters. No constraints or relationships between parameters are explained.

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 'Add' and the resource 'cause to a Fishbone category', distinguishing it from siblings like rc_add_causal_link or rc_init_fishbone. It also lists optional attributes (sub-causes, evidence, HFACS classification), making the tool's function precise and 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 does not specify when to use this tool versus alternatives (e.g., rc_add_causal_link). No context about prerequisite actions (like initializing a session or fishbone) or typical workflow is provided, leaving the AI agent to infer usage 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.

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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions that archived sessions are preserved but marked inactive, but does not disclose potential side effects, reversibility, permissions required, or impacts on related data.

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

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

The description is a single succinct sentence that front-loads the key information. Every word contributes meaning, and there is no unnecessary detail.

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

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

For a simple tool with one parameter and no output schema, the description is minimally adequate. However, it lacks details about the behavior of archiving (e.g., whether it can be undone, impact on list views, or related links).

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

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

Schema coverage is 100% for the single parameter 'session_id', and the description adds no additional meaning beyond the schema. The baseline score of 3 is appropriate.

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

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

The description clearly states that the tool archives a completed RCA session, specifying the resource (RCA session) and action (archive). However, it does not differentiate from sibling tools, but since no other archive tool exists, this is acceptable.

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 only implies that the session should be completed before archiving, but does not provide explicit guidance on when to use this tool vs alternatives, nor does it mention any prerequisites or exclusions.

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?

With no annotations provided, the description takes on the full burden. It discloses the key behavioral aspect: each call goes one level deeper up to 5 levels. It does not describe the output format or what happens after the 5th level, but overall it is fairly transparent.

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 three sentences, each earning its place: first states purpose, second explains behavior with constraints, third emphasizes importance. No fluff.

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 no output schema and no annotations, the description should hint at the return value. It does not describe what the tool returns after each call. It covers the reasoning flow well but omits output expectations, making it slightly incomplete.

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

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

Schema coverage is 100%, so the schema already documents each parameter. The description adds value by explaining the role of 'initial_problem' (required only for first Why) and the default behavior of 'parent_node_id', which clarifies usage 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 action ('Ask Why?'), the resource ('drill down into root causes using 5-Why analysis'), and distinguishes from siblings by labelling itself 'the CORE tool for systematic root cause reasoning.'

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 explains that each call goes one level deeper (up to 5 levels) and that it creates or extends a WhyChain, giving clear context for when to use it. However, it does not explicitly mention when not to use it or compare to alternative tools like rc_add_cause or rc_get_why_tree.

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?

No annotations are provided, so the description bears full responsibility. It describes outputs but does not disclose side effects (e.g., whether the tool modifies the session), required permissions, or any limitations. The behavior is not fully transparent.

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?

Two sentences with no wasted words. The main purpose is front-loaded, and every sentence adds value by listing outputs.

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 3 parameters with 100% schema coverage and no output schema, the description adequately explains the tool's function and outputs. However, it could be more specific about the output format (though format param exists) and does not state dependencies like authentication or session validity.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add additional meaning beyond the schema; the parameters are straightforward, and the description focuses on outputs rather than parameter semantics.

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 specifies the verb 'Transform' and the resource 'completed Why Tree into a teaching-ready lesson plan', and lists the generated outputs (learning objectives, pitfalls, etc.). It clearly distinguishes from sibling tools like export functions.

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 implies the tool should be used when a Why Tree is completed, but does not explicitly state when to use it versus alternatives like rc_export_why_tree, nor does it provide exclusions or prerequisites beyond the tree being complete.

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?

No annotations are provided, so the description carries the full burden. It discloses that confirmed classifications are stored as learned rules, which is a key behavioral trait (side effect). This helps the agent understand the learning impact. It could mention irreversibility or permission requirements, but the disclosure is adequate.

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 consists of two concise, front-loaded sentences with no wasted words. Every sentence adds value: action statement, learning purpose, and storage behavior.

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 lack of output schema, the description does not explain the return value, but the action is simple. It covers the core purpose and key behavior. It could mention that the tool requires a prior suggestion or that the reason parameter is used for traceability, but it is sufficiently complete for a straightforward confirmation 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 coverage is 100%, so each parameter already has a description. The tool description adds no additional meaning beyond what the schema provides, earning the 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 'Confirm an HFACS classification as correct' and specifies the resource. It explains the higher-level purpose: helping the system learn and improving future suggestions, distinguishing it from sibling tools like rc_suggest_hfacs and rc_list_learned_rules.

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

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

The description implicitly indicates that this tool should be used when a classification needs to be confirmed and stored as a learned rule. It provides context for learning but does not explicitly state when not to use it or mention alternatives. However, given sibling tools, the usage is clear.

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?

With no annotations provided, the description only hints at non-destructive behavior (export) but does not disclose details like whether the session must be active, potential side effects, or error conditions.

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 extremely concise with two short sentences, no unnecessary details, and front-loaded with the core purpose.

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

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

For a simple two-parameter tool with no output schema, the description is adequate but incomplete: it does not specify the output format or behavior on errors, which would be helpful.

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

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

Schema coverage is 100% with descriptions for both parameters. The description adds context by listing the supported formats, which matches the enum, but does not provide additional meaning 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 tool exports a Fishbone diagram in specific formats (Mermaid, JSON, Markdown), which distinguishes it from sibling tools like rc_get_fishbone (retrieves data) and rc_export_why_tree (exports a different diagram type).

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?

No guidance is provided on when to use this tool versus alternatives like rc_get_fishbone or rc_export_why_tree. The description lacks context about prerequisites or scenarios.

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?

No annotations are provided, so the description must fully convey behavior. It states 'Export' but does not specify if the operation is synchronous, generates a file, returns a string, or has any side effects. The behavioral details are minimal.

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?

Two concise sentences covering the essential action and supported formats. No unnecessary words or repetition.

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?

Lacks critical info about the output: does the tool return a downloadable file, a string, or something else? Without an output schema, the description should clarify the nature of the export result.

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

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

Schema coverage is 100% and clearly describes both parameters. The description simply echoes the format options, adding no new semantic depth beyond what the enum already provides.

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

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

The description clearly states the tool exports a 'Why Tree' and lists the supported formats (Mermaid, JSON, Markdown). It distinguishes from sibling tools like rc_get_why_tree (retrieval) and rc_export_fishbone (different diagram type).

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

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

The purpose is clear but no explicit guidance on when to use this tool versus alternatives like rc_get_why_tree for retrieval or other export tools. Usage is implied but without conditional or exclusionary 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?

No annotations provided, so description carries full burden. States it provides mapping and Why Tree depth guidance, but lacks details on permission requirements, rate limits, or response format. Adds value beyond schema but not extensive.

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?

Three sentences, front-loaded with action, no wasted words. Efficiently covers purpose, details, and context.

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?

Without output schema, description adequately explains the type of information returned (mapping and depth guidance). Given low complexity, it is sufficiently complete, though could elaborate on the output structure.

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

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

Schema coverage is 100% with parameter description already explaining the default behavior. Description does not add new information about parameter beyond what schema provides, so baseline 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?

Description clearly states the tool retrieves mappings between 6M Fishbone categories and HFACS codes, lists all six categories, and explains it shows correspondence. This distinguishes it from sibling tools like rc_get_fishbone or rc_get_hfacs_framework.

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?

Indicates use for cross-framework analysis and comprehensive coverage, giving clear context. Does not explicitly state when not to use or compare to siblings, but the purpose is sufficiently clear for appropriate selection.

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?

No annotations exist, and the description only indicates it returns the diagram. It does not disclose whether the operation is read-only, behavior on invalid session IDs, or any side effects. The 'get' prefix implies idempotency but is not explicitly stated.

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?

Two sentences efficiently convey purpose and output. Every word is necessary with no fluff or 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?

For a simple getter with one parameter and no output schema, the description is minimally adequate. It lacks details on output structure, error handling, and how it differs from similar retrieval tools among 20+ siblings.

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?

There is one parameter (session_id) with 100% schema coverage. The description adds no additional meaning beyond the schema's 'The session ID' – no format, examples, or constraints. Baseline 3 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 retrieves the complete Fishbone diagram for a session, returning all categories and causes in a structured format. It uses specific verbs and resource naming, and implicitly distinguishes from export or other retrieval tools like rc_get_why_tree.

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?

No guidance on when to use this tool versus alternatives such as rc_get_session or rc_get_why_tree. The description does not provide any exclusions, prerequisites, 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.

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

No annotations provided; description implies a read operation but does not explicitly state read-only nature, response details, or any constraints beyond parameter behavior.

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?

Two short sentences, front-loaded with purpose, no extraneous 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?

For a simple retrieval tool with one optional parameter and no output schema, the description fully covers purpose and parameter semantics.

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

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

Schema coverage is 100%, baseline 3. Description adds clarity by noting the default behavior when not specified ('returns all levels'), which goes beyond 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?

Description clearly states the tool retrieves the HFACS-MES framework structure and category definitions, with a specific verb ('Get') and resource. It distinguishes from sibling tools that add causes or links.

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?

Description suggests using it to understand classification hierarchy but does not explicitly state when to use vs alternatives 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.

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

No annotations are provided, so the description carries full burden. It states the tool returns session status, stage, and progress, but does not disclose whether it is read-only, idempotent, or any potential side effects. Basic behavioral context is present, but not comprehensive.

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

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

The description is a single sentence that efficiently conveys the purpose and output. It is front-loaded with the action and resource, with no redundant or extraneous content.

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 simple retrieval tool with one parameter, the description adequately covers what it does and what it returns. It does not address error handling or edge cases, but given the low complexity, it is reasonably 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?

Schema coverage is 100% with a single parameter 'session_id' described as 'The session ID to retrieve'. The description adds no additional meaning, constraints, or examples beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states the tool retrieves session details by ID and specifies the returned data (status, stage, progress). It distinguishes itself from sibling tools like rc_list_sessions (which lists sessions) and rc_start_session (which creates).

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

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

The description does not explicitly state when to use this tool versus alternatives (e.g., after obtaining a session ID from rc_list_sessions). It lacks guidance on prerequisites, exclusions, or context for when this tool is appropriate.

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?

No annotations are provided, so the description must convey behavioral traits. It describes a read operation (get, shows) and implies no side effects, but does not explicitly state it is non-destructive or discuss permissions. This is acceptable for a simple retrieval but not fully transparent.

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?

Two concise sentences that front-load the core action and output. Every sentence adds value with no redundancy or extraneous 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 single parameter, no output schema, and low complexity, the description sufficiently explains what the tool returns. The sibling list adds context, but the description alone is adequate for a simple retrieval 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?

The parameter 'session_id' is already described in the schema with full coverage. The description adds no further meaning about the parameter format or constraints beyond what the schema provides, meeting the baseline.

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 it gets the complete Why Tree for a session, specifying the format (5-Why analysis chain, hierarchical). This differentiates it from sibling tools like rc_get_fishbone or rc_export_why_tree.

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?

No explicit guidance on when to use this tool versus alternatives like rc_get_fishbone or rc_get_hfacs_framework. The context implies it is for viewing the Why Tree but lacks exclusions or prerequisites.

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?

No annotations provided, and description does not disclose behavioral traits such as idempotency, side effects on existing fishbone for the same session, or required permissions. For a mutation tool, this 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.

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

Two sentences that front-load the core purpose and key structural detail (6M categories). No redundant words. Efficient and clear.

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 the main action and structure created. For a parameter-light, no-output-schema tool, it is mostly complete. However, could mention what happens if a fishbone already exists for the session (overwrite vs error) and return behavior.

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

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

Schema coverage is 100% and both parameters have descriptions (session_id and problem_statement) that explain their roles. The tool description adds context about the 6M structure but does not enhance parameter-level meaning 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?

Clearly states the verb 'Initialize' and describes creating a Fishbone diagram with a 6M structure and problem statement as fish head. Distinguishes from siblings like rc_get_fishbone (retrieval) and rc_add_cause (modification).

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?

Implied usage (for starting a new fishbone diagram) but no explicit guidance on when to use vs siblings like rc_start_session or rc_get_fishbone. Lacks 'when not to use' or alternative suggestions.

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 discloses that only rules confirmed by experts are returned, which is a key behavioral trait. However, with no annotations, it lacks details on authorization, pagination, or complete behavior. The description adds value beyond annotations but is not thorough.

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 very concise with two short sentences, front-loading the purpose. Every word earns its place, though a bit more structure (e.g., bullet points) could improve scannability.

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 no output schema and two simple filters, the description is adequate but could mention return format, sorting, or pagination. It provides enough context for a basic list tool but lacks completeness for complex scenarios.

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

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

Schema description coverage is 100% (both parameters have descriptions in the schema). The tool description does not add any additional meaning beyond what the schema already provides, so it meets the baseline 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 uses the specific verb 'List' and identifies the resource as 'learned classification rules', adding that these are confirmed by experts. This clearly distinguishes it from sibling tools like rc_reload_rules or rc_suggest_hfacs.

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 implies usage for viewing confirmed rules but provides no explicit guidance on when to use this tool versus alternatives such as rc_get_hfacs_framework or rc_get_session. No prerequisites or exclusions are mentioned.

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?

No annotations are provided, and the description only says 'Returns summary of all sessions'. It does not disclose behavioral traits such as side effects, authentication needs, or rate limits. For a read-only list tool, this 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.

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

The description is concise with two front-loaded sentences. Every word is necessary and 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?

Given the low complexity of a list tool with optional filters, the description adequately covers the purpose and return type. However, with no output schema, it could briefly mention that it returns a summary (not full details), which it does. Nearly 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?

Schema coverage is 100% with clear parameter descriptions in the input schema. The description only adds 'with optional filters' which adds no extra meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states 'List all RCA sessions with optional filters', providing a specific verb (list) and resource (RCA sessions). It distinguishes itself from siblings like rc_get_session by implying a list versus a single session.

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 implies usage for listing sessions but does not explicitly state when to use it versus alternatives or provide any exclusion criteria. No guidance on when not to use it.

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

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

With no annotations provided, the description carries the full burden. It only says it 'indicates the analysis has reached a fundamental cause that requires action', but does not disclose what changes occur, e.g., if the node is locked, if effects are reversible, or if confirmation is needed.

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?

Two sentences, front-loaded with the action, no extraneous words. Every sentence earns its place.

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 3 parameters, no output schema, and no annotations, the description is minimally adequate but lacks behavioral and usage context that would fully inform an agent.

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

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

Schema coverage is 100%, so baseline is 3. The description does not add any meaning beyond the schema—it doesn't explain the confidence parameter or how to choose the node_id.

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 'Mark' and the resource 'WhyNode as the identified root cause', and distinguishes this from sibling tools like rc_add_cause or rc_confirm_classification by specifying the action of marking the root cause.

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

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

The description provides no guidance on when to use this tool vs alternatives, such as rc_confirm_classification or rc_add_cause. It does not specify prerequisites or situations where marking a root cause is appropriate.

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?

With no annotations provided, the description bears full responsibility for disclosing behavior. It states the action (reload from YAML) but does not mention potential side effects (e.g., overwriting existing rules, validation errors). The description is adequate but lacks depth about what happens during reload.

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 consists of two concise sentences with no unnecessary words. It is front-loaded with the core purpose and provides usage context, making it highly 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?

For a simple tool with no parameters and no output schema, the description covers the essential purpose and usage. It could mention potential outcomes (e.g., success messages, error handling) but is still reasonably complete for the task.

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 zero parameters and 100% coverage (since none exist). The description does not need to add parameter information. Following the baseline rule for zero parameters, a score of 4 is appropriate.

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

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

The description clearly states the action ('Reload') and the resource ('classification rules from YAML files'), distinguishing it from sibling tools that add, confirm, or export classifications. It uses a specific verb and resource, making the purpose 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 explicitly states when to use the tool: 'after manually editing config files.' This provides clear context for usage, though it does not mention when not to use it or list alternatives. The guidance is sufficient for this simple action.

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?

No annotations exist, so the description must disclose side effects and behaviors. It only states 'creates a new session' without mentioning auth requirements, potential conflicts, or whether the session is persisted. Minimal transparency for a creation operation.

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?

Two sentences, no wasted words. Could be slightly improved with structured format (e.g., listing return value separately), but overall concise and clear.

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?

Explains return value despite no output schema, but missing details on error cases, validation rules for case_type enum, and what happens if required fields are missing. Adequate but not complete for a tool with 3 parameters.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by mentioning return of session_id, but does not elaborate on parameter meaning beyond schema definitions.

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

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

Description clearly states it starts a new RCA analysis session with specified case type and title, and returns session_id. This is specific and distinguishes from sibling tools like rc_list_sessions or rc_get_session.

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?

Implied usage as the initial step for RCA analysis, but no explicit guidance on when to use versus alternatives like rc_list_sessions or rc_archive_session. No exclusion criteria provided.

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?

No annotations provided, so the description must carry full burden. It states the tool returns ranked suggestions with confidence scores and lists HFACS-MES levels, but lacks details on side effects, permissions, or output specifics like the format of suggestions.

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 concise at two sentences, front-loading the purpose. It efficiently conveys the key function and context, though it could incorporate usage guidelines without adding much length.

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

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

With no output schema, the description provides high-level output info (ranked suggestions with confidence scores) and lists HFACS-MES levels. However, it does not explain confidence scoring or return structure, leaving some gaps in completeness.

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

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

All three parameters have descriptions in the input schema (100% coverage). The tool description does not add extra meaning beyond the schema, so baseline score of 3 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?

Clearly states the tool suggests HFACS-MES classification codes for a cause description and returns ranked suggestions with confidence scores. The description differentiates from sibling tools which involve adding causes, links, sessions, etc.

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?

No explicit guidance on when to use this tool versus alternatives like rc_confirm_classification or rc_get_hfacs_framework. The description does not mention prerequisites or exclusions.

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?

No annotations are given, so the description carries full burden. It details the four tests but omits behavioral traits like side effects, idempotency, required permissions, or what happens on invalid input. It partially compensates with internal logic but lacks safety/state context.

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 two sentences, front-loaded with purpose, and uses a clear list format. Every sentence is informative. Loses a point for lacking structured formatting (e.g., line breaks for the list) but overall 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?

No output schema is provided, and the description does not explain what the tool returns (e.g., boolean, scores). It also does not describe how session_id is used or caveats about nested objects. Lacks completeness for an agent to invoke 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 coverage is 100%, so baseline is 3. The description lists the four tests but does not explicitly link them to parameters. The verification_level parameter is already well-described in the schema. The description adds marginal value beyond 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 'Verify' and the resource 'causal relationship', and lists four specific tests. This distinguishes it from sibling tools like rc_add_causal_link or rc_confirm_classification.

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?

No explicit guidance on when to use this tool vs alternatives. Sibling tools exist but no differentiation criteria are provided. The tests imply a verification scenario, but 'when-not' and alternatives are missing.

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