VerifiMind PEAS - RefleXion Trinity

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

With no annotations, the description carries the transparency burden. It discloses BYOK behavior, key auto-detection, and that keys are ephemeral ('never stored' and 'garbage collected'), which is valuable behavioral context. It doesn't elaborate on all side effects, but the information provided is meaningful and non-contradictory.

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

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

The description is well-structured with a clear opening, a bulleted specialization list, and a concise BYOK section. It is slightly longer than necessary due to the version number and detailed key-handling explanation, but every part serves a purpose and the main function is front-loaded.

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

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

The tool has 8 parameters and an output schema, and the description explains the tool's purpose and BYOK flow. However, it does not explain parameters like 'detail' (which has a default but no description), 'user_uuid', or 'prior_reasoning' beyond their schema hints, leaving some gaps for a moderately complex 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 description adds significant meaning beyond the schema, especially for llm_provider and api_key: it explains how to pass them for BYOK and auto-detection. Schema coverage is 75%, so most parameters are already described; the description supplements rather than repeats, and it gives conceptual context for security-related inputs.

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 consults a CS Security agent for 'security validation and Socratic interrogation', with a bulleted list of security specialties. This distinguishes it from sibling agents like consult_agent_x and consult_agent_z by explicitly focusing on security assessment.

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 specialization list implies when to use (security vulnerability assessment, attack vectors, data security, etc.) and describes the tool's Socratic questioning approach. However, it does not explicitly state when not to use it or name alternative tools, so it falls short of a perfect score.

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, the description carries the full burden of behavioral disclosure. It transparently explains the BYOK mechanism, including how to pass llm_provider and api_key, auto-detection from key prefix, and the ephemeral nature of keys (never stored, garbage collected). However, it does not disclose other potential behaviors like rate limits, error handling, or side effects, but the key transparency is valuable.

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

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

The description is well-structured with a clear opening sentence, a bulleted list of specializations, and a concise BYOK section. It is appropriately sized, with no redundant text. Every sentence adds value, and the layout makes it easy to scan.

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

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

Given the tool's complexity (7 parameters) and the existence of an output schema, the description covers the core purpose, specializations, and BYOK behavior succinctly. It does not explain the return format, but that is handled by the output schema. It could improve by explicitly differentiating from sibling agents and providing usage conditions, but overall it is fairly complete.

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

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

Schema description coverage is 71%, so the schema already documents most parameters. The description adds meaningful semantics for llm_provider and api_key by explaining the BYOK behavior, auto-detection, and ephemerality, which go beyond the schema's brief descriptions. It also gives context to concept_name and concept_description through the specialization list, though those are already well-defined in 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's purpose: 'Consult X Intelligent agent for innovation and strategy analysis.' It uses a specific verb ('Consult') and resource ('X Intelligent agent') and outlines five distinct specialization areas, which differentiates it from sibling agents like consult_agent_cs and consult_agent_z.

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 innovation and strategy analysis through the specialization list, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or conditions. The context is clear but lacks explicit guidance on when not to use it or which sibling might be more 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 carries full burden. It discloses the agent's veto power and its consequence ('If veto_triggered is True, the concept should not proceed'), the BYOK key handling ('Keys are ephemeral (never stored) and garbage collected'), and the list of ethical review areas. This is more transparent than typical descriptions.

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

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

The description is well-structured: a one-sentence purpose, a concise bullet list of specialties, a clear warning about veto power, and a compact BYOK note. Each section contributes distinct information without empty filler.

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

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

The description covers the tool's purpose, key behavioral traits, and BYOK usage. Given that an output schema exists and the required parameters are self-explanatory from the schema, the description provides sufficient context for an agent to use the tool correctly. It could mention workflow integration, but that's not necessary.

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

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

The schema already documents most parameters with descriptions (75% coverage). The description adds context for llm_provider and api_key, explaining the BYOK flow, auto-detection from key prefix, and ephemerality. It doesn't elaborate on parameters like detail or user_uuid, but they are either simple or schema-documented.

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 a specific verb ('Consult') and identifies the resource ('Z Guardian agent') and its function ('ethical review and Z-Protocol enforcement'), with a bulleted list of specializations that clearly distinguishes it from siblings like consult_agent_x and consult_agent_cs.

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 clearly states the tool's purpose and specialties, indicating it is for ethical review and Z-Protocol compliance. It does not explicitly mention when not to use it or compare to alternative agents, but the focused list of capabilities provides clear 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?

With no annotations provided, the description carries the full burden and excels: it discloses the security incident, that the tool always returns a denial, that all arguments are ignored, and that nothing is stored or returned. This is exemplary transparency about the tool's operational state.

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 and well-structured. It front-loads the purpose, then the status, reason, guidance, and result in clear paragraphs. Every sentence adds essential information, with no redundancy or filler.

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

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

The tool has 9 parameters and an output schema, but the current behavior is fully described: it always returns a specific error. The description explains the security incident, the containment actions, and the expected return type. Nothing relevant is missing for the agent to correctly avoid wasting time on this tool.

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

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

Schema coverage is 0%, but the description compensates completely by stating 'All arguments are accepted for schema stability and are ignored; no supplied value is stored, logged, or echoed back.' This tells the agent that parameter values are irrelevant, which is essential given the tool is disabled.

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 intended purpose: 'Create a structured MACP v2.5 handoff record.' It immediately discloses the tool is temporarily disabled and always returns a denial, making the current behavior unmistakable. This distinguishes it from the sibling read tool.

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

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

The description explicitly explains when not to use the tool: it is disabled, and 'Coordination state belongs in your own repository until private, owner-scoped storage ships.' This provides clear context and a practical directive, though it does not name a specific alternative tool. It fully conveys that using it now is pointless.

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, the description carries the full burden and does exceptionally well. It discloses the security vulnerability (VM-IR-2026-07-28-COORD-01), the fact that all arguments are ignored, that no record body is returned, and the exact error type returned (COORDINATION_TEMPORARILY_DISABLED).

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

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

The description is well-structured: a clear one-sentence purpose, followed by the disabled status, the reason, operational detail, and return behavior. Each section earns its place, and the security incident reference adds necessary context without wordiness.

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

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

The description fully covers what the tool does, its current operational state, parameters, and return behavior. Given the output schema exists and the tool is disabled, the description is complete—it explains everything an agent needs to know, including the fact that no record body will ever be returned.

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?

Despite 0% schema description coverage, the description explicitly states 'All arguments are accepted for schema stability and are ignored.' This is the critical semantic addition—agents know not to bother populating count, agent_id, or pioneer_key because they have no effect.

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

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

The description opens with a specific verb and resource: 'Read the most recent coordination handoff record(s).' This clearly distinguishes it from sibling tools like coordination_handoff_create, which writes, and consult_agent_* tools, which serve a different consulting purpose.

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

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

The description explicitly states the tool is TEMPORARILY DISABLED and 'always returns a denial,' making it unambiguous that it should not be used. It also mentions the security incident and that it is closed to every caller, leaving no doubt about usage status.

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, the description carries the full transparency burden. It discloses the security incident (VM-IR-2026-07-28-COORD-01), the lack of authenticated ownership check, the denial behavior, and the exact error type returned. This fully informs the agent of behavioral outcomes.

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

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

The description is well-structured and front-loaded with the critical disabled status. Every sentence adds necessary context: the security incident, why it is closed, that parameters are ignored, and the return behavior. No redundant information exists.

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

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

Given the tool's disabled state, the description is complete. It explains the cause, the scope of the shutdown, that all arguments are ignored, and what response the caller will receive. An agent has all information needed to avoid misuse.

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

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

Schema description coverage is 0%, but the description explicitly states 'All arguments are accepted for schema stability and are ignored.' This fully explains the behavior of the single parameter (pioneer_key), compensating for the missing schema-level description.

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

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

The description clearly states the tool's purpose: it was designed to 'Return current team coordination state and session summary' but is now explicitly 'TEMPORARILY DISABLED' and 'always returns a denial.' This makes the current behavior unambiguous and distinguishes it from all sibling tools by marking it as non-functional.

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 explicit when-not-to-use guidance: 'It is closed to every caller while owner-scoped access control is rebuilt.' It also clarifies that all arguments are ignored, so no invocation should be attempted with meaningful parameters. This is stronger than typical usage guidance.

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

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

With no annotations, the description carries the full burden for behavioral disclosure. It mentions the export formats but does not state whether the operation is read-only, what permissions are required, or how the exported content is returned. Side effects and error conditions are unaddressed.

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 core sentence is concise, but the trailing 'v0.4.0 Unified Prompt Templates feature' adds no functional value and clutters the description. It is not zero-waste.

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?

Despite an output schema and three parameters, the description is too brief to guide selection fully. It does not differentiate from get_prompt_template or explain the role of user_uuid, leaving the agent underinformed for a tool with several 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?

Schema description coverage is 67%; format and template_id are described, but user_uuid is not. The description adds no detail about user_uuid or clarifies parameter semantics beyond the schema. The format mention duplicates the schema's format description.

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 ('Export'), the resource ('prompt template'), and the acceptable formats ('Markdown or JSON'). This distinguishes it from sibling tools like get_prompt_template, which likely retrieves rather than exports.

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 use when an export of a prompt template is needed, but it does not explicitly state when to prefer this over alternatives like get_prompt_template or list_prompt_templates. No exclusions or alternative references are 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 are provided, so the description carries the full burden. While 'Get' implies a read operation, the description does not disclose behavior such as how include_content affects the response, what happens when a template is not found, or any side effects. The version note is irrelevant to 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?

The description is very short and front-loaded, with the primary purpose in the first sentence. However, the second sentence 'v0.4.0 Unified Prompt Templates feature' is extraneous and provides no operational value, slightly reducing conciseness.

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

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

The tool is simple and has an output schema, but the description lacks usage guidelines and does not address all parameters (especially user_uuid). It is minimally complete for a basic get-by-ID operation, but not fully sufficient for an agent to handle edge cases or choose among 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?

The schema descriptions cover template_id and include_content, but user_uuid has no description. The tool description does not clarify any parameters or add meaning beyond the schema; it merely reiterates the ID concept, leaving the user_uuid parameter underspecified.

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 'Get a specific prompt template by ID' clearly specifies the verb (Get), resource (prompt template), and unique identifier (ID), distinguishing it from sibling tools like list_prompt_templates and export_prompt_template.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives like list_prompt_templates or export_prompt_template. Usage is only implied by the phrase 'by ID', but there is no clear context or exclusion criteria.

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 of behavioral disclosure. It mentions version 0.4.0 but does not disclose whether the operation is read-only, any permission requirements, or data scope implications (e.g., how user_uuid affects the results).

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 and front-loaded with the primary purpose. However, the version note 'v0.4.0 Unified Prompt Templates feature' adds little operational value and could be removed, slightly reducing conciseness.

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?

Despite having an output schema, the description omits critical context such as the meaning of user_uuid and when to use the tool. The low parameter coverage and lack of usage guidance make it incomplete for effective tool selection.

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

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

The schema describes a single optional parameter user_uuid with no description coverage. The tool description does not mention this parameter at all, leaving its purpose and effect completely undocumented.

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

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

The description clearly states the tool's function: retrieving statistics about the template registry. It specifies the type of statistics (counts by agent, phase, and type), which distinguishes it from sibling tools that retrieve individual templates or list them.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives like list_prompt_templates or get_prompt_template. It only states what it does, leaving the agent to infer usage 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 are provided, so the description carries full burden. It states the action but does not disclose side effects such as whether the import creates a new template, overwrites existing ones, or requires authentication. The 'Unified Prompt Templates feature' note adds no behavioral detail.

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 compact and front-loaded with the primary action, followed by a brief list of supported URL types. The version note 'v0.4.0 Unified Prompt Templates feature' is minor extra context but not strictly necessary.

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 an output schema present, return values are covered. However, the description lacks information on the import behavior (e.g., persistence, overwrite policy) and the 'user_uuid' parameter is ambiguous. It is adequate but not comprehensive.

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

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

The schema covers 67% of parameters with descriptions. The description adds detail about acceptable URL formats for the 'url' parameter, but 'validate' and 'user_uuid' remain unexplained in both schema and description. The added URL context prevents a score below 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 'Import' with a resource 'prompt template' and source 'URL', clearly distinguishing it from sibling tools like export_prompt_template and list_prompt_templates. The supported URL types add specificity.

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

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

The description provides clear context on acceptable input types (GitHub Gist, raw file, HTTPS JSON/YAML), which informs when this tool is appropriate. However, it does not explicitly mention alternatives or when not to use, leaving some inference to the agent.

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 of behavioral disclosure. It only restates the purpose ('List available prompt templates') and adds a version note, but does not disclose filtering semantics, ordering, pagination, output shape, or any access considerations. This is minimal beyond the name itself.

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 short sentences with no filler. The first sentence is the core functional statement, and the version note is brief and unobtrusive. It is appropriately sized for its simplicity.

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

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

The tool has four optional parameters, an output schema, and multiple sibling tools, but the description is extremely sparse. It fails to clarify how this listing tool relates to get_prompt_template or export_prompt_template, does not mention return behavior, and gives no context about the unified prompt templates feature beyond a version string. This is incomplete for effective agent selection.

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

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

The input schema already documents three of four parameters (tags, agent_id, category) with descriptions, giving 75% coverage. The description only gestures at 'optional filtering' without elaborating on specific parameters, and user_uuid remains undocumented. The schema does the main work, so the description adds little semantic value.

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

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

The description clearly states the tool lists available prompt templates with optional filtering. The verb 'List' plus the resource 'prompt templates' precisely defines the operation, and the presence of sibling tools like get_prompt_template and export_prompt_template makes the distinguishing scope evident.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention that get_prompt_template is for retrieving a single template or that export_prompt_template is for exporting, so the agent receives no explicit decision-making support.

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 of behavioral disclosure, but it only states the action without revealing side effects, permissions, return behavior, or what happens to existing templates. The version note adds no 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 very concise with one sentence plus a version note, containing no fluff. However, it may be too terse; the version note 'v0.4.0 Unified Prompt Templates feature' is minimally useful but not wasteful.

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

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

Given the tool has 7 parameters, no annotations, and an output schema, the description is too sparse to be contextually complete. It lacks guidance on when to use it, behavioral expectations, and any clarification beyond the schema.

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 high (86%), so the schema already explains most parameters. The description adds no additional meaning about parameters, leaving it at the baseline score.

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

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

The description clearly states the action 'Register a new custom prompt template' with a specific verb and resource. It distinguishes from sibling tools like get_prompt_template, list_prompt_templates, export_prompt_template, and import_template_from_url by focusing on creating a new template via registration.

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 adding a new custom template, but provides no explicit guidance on when to use this tool versus alternatives like import_template_from_url. No exclusions or alternative scenarios 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?

With no annotations, the description supplies useful behavioral context: agents run sequentially, each sees previous reasoning, results are synthesized, and BYOK keys are ephemeral, never stored, and garbage collected. It could also disclose history/save side effects, but the included traits go well beyond a bare statement.

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

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

The description is well-organized with a numbered pipeline and a compact BYOK paragraph. It is slightly repetitive—'Each agent sees the reasoning of previous agents' restates the bullet details—but every major point is scannable and front-loaded.

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

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

Given the tool's complexity (14 params, 3-agent orchestration) and a rich schema, the description covers the essential flow and authentication model. It does not mention the detail or save_to_history behaviors, but those are already covered in the schema, and the output schema exists, so the description is adequate.

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

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

Schema coverage is 93%, so the schema already documents most parameters. The description adds meaningful semantics by explaining the global vs per-agent BYOK parameters and that per-agent overrides take priority over global, which is not stated in the 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 opens with a specific verb+resource ('Run complete X → Z → CS Trinity validation with Chain of Thought') and then enumerates the three-agent sequence. This clearly differentiates it from sibling consult_agent_x/z/cs tools, which handle individual agents.

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 says this tool runs the complete pipeline and orchestrates all three agents in sequence, making it clear this is the full-validation path. It does not name alternative tools or state when not to use it, but the context is sufficiently clear for selection among the sibling tools.

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