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

With no annotations, the description must disclose behavioral traits. It implies a read-only analysis but does not explicitly state side effects, return format, or how recommendations are delivered. Important details about expected output and runtime behavior are missing.

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 front-loaded sentence with no fluff. Every word earns its place, making it appropriately concise.

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

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

The tool accepts a complex nested context object, but the description does not explain what the agent should expect as output, how the analysis informs template selection, or why it is preferable to sibling tools. It is minimally adequate.

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

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

The schema gives a basic description for the single parameter ('Project context to analyze') and exposes nested fields. The tool description adds no extra meaning beyond that, so the baseline of 3 applies given high schema coverage.

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 ('Analyze'), the resource ('project context'), and the outcome ('recommend suitable templates and improvements'). It distinguishes the tool from siblings that list or search templates, though 'improvements' is somewhat vague.

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 over alternatives such as search_templates or generate_prp. There are no use-case hints, exclusions, or references to sibling tools.

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 carry the behavioral disclosure burden. It only says 'Create' without mentioning side effects, permissions, reversibility, or what happens on duplicate names. This is a minimal and insufficient disclosure for a mutation tool.

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

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

The description is a single, concise sentence that front-loads the verb and resource. Every word earns its place, and there is no unnecessary elaboration.

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 tool with no output schema and no annotations, the description is too sparse to provide complete context. It fails to mention return values, creation behavior, or the significance of nested sections, leaving the agent with limited understanding 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?

The schema description coverage is 100%, with all five parameters described directly in the input schema. The description adds no semantic information about parameters, but the schema already provides detailed meaning, so 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 states 'Create a new custom PRP template' with a clear verb and object, making the tool's purpose obvious. It distinguishes from sibling tools like list_templates and search_templates, but it does not explicitly contrast with potential 'create' variants or explain the 'PRP' term.

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 lacks any context about prerequisites, appropriate scenarios, or comparisons to list_templates or update_prp.

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 carry the full burden. It only vaguely mentions 'storage integration' but does not disclose that saveToStorage defaults to true, that Archon integration or task creation may occur, or any side effects/return 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 one sentence, front-loaded with the action and object, and contains no fluff or repeated information from the schema.

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 (12 parameters, nested objects, multiple integration flags) and no output schema or annotations, the one-sentence description is insufficient. It omits integration behavior, output/return details, and deeper guidance for correct invocation.

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 tool description adds only general context (template, project context, storage integration) and does not enrich specific parameter semantics 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 generates a Product Requirements Prompt from a template and project context, with storage integration. This distinguishes it from siblings like validate_prp, list_prps, and update_prp.

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 use case: generating a PRP from an existing template and project context. It does not explicitly name alternatives or exclusions, but the context is clear enough when compared to sibling tools.

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. 'List and search' implies a read operation, but it does not explicitly state that it is safe, describe pagination behavior, or mention that includeStats and includeArchonStatus may trigger additional workload or external calls. The description is too thin to convey meaningful behavioral information.

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, well-formed sentence with no redundancy or fluff. It is appropriately concise and front-loaded with the core action and resource, though the phrase 'advanced filtering and sorting capabilities' is somewhat generic and could be more specific.

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 10 parameters, nested objects, and no output schema, yet the description is only one line. It does not explain what PRPs are, what 'advanced filtering' entails, or what kind of results the agent should expect. The context provided by sibling tools suggests PRPs are a known entity, but the description itself is insufficient for a tool of this complexity.

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 provides 100% description coverage for all 10 parameters, including defaults and enums, so the baseline is 3. The description's reference to 'advanced filtering and sorting capabilities' adds minimal semantic value beyond what the schema already documents, and does not explain parameter relationships or usage patterns.

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 identifies the verb (list and search) and the resource (PRPs), and distinguishes from sibling tools like list_templates by resource type. However, it lacks any definition or expansion of what PRPs are, which slightly reduces clarity.

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 such as generate_prp, update_prp, or search_templates. The description does not mention prerequisites, exclusions, or comparative scenarios, leaving the agent without decision 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?

No annotations are provided, so the description carries full burden. It does not disclose any behavioral traits such as whether this is a read-only operation, pagination limits, or response format. The description is too brief to provide meaningful transparency beyond the basic action of listing.

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?

A single, clear sentence that front-loads the core action and resource. Every word earns its place, with no redundancy or filler.

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

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

The tool is low-complexity with one optional parameter and no output schema. The description adequately conveys that it returns a list of available templates, but it does not specify the return fields or any limitations (e.g., pagination). For a simple read tool, this is sufficient but not rich.

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 100% of parameters with descriptions, so the description adds little beyond what the schema already provides. The mention of 'optional filtering by category' aligns with the schema but introduces no new semantic detail.

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

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

The description uses a specific verb 'list' with a clear resource 'PRP templates' and mentions optional category filtering. It distinguishes itself from sibling tools like 'search_templates' (which implies broader searching) and 'list_prps' (likely a different resource).

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 when you need to list templates, but it does not explicitly state when to choose this over alternatives like search_templates. There is no exclusion or when-not-to-use guidance, but the intended use is reasonably clear from the context.

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

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

With no annotations, the description must disclose behavioral traits. It fails to mention that actions like rollback, delete_prp, or resolve_conflict are likely destructive or have side effects. It also does not note prerequisites, permission needs, or return behavior. The phrase 'Manage storage operations' gives almost no behavioral insight.

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 12-word sentence, which is concise and front-loaded. However, it lacks structure and substance, providing only a high-level category list without examples or concrete details. It is efficient but under-specifies.

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 complex (19 parameters, 9 distinct actions, no output schema, no annotations), yet the description is far too brief. It does not explain how actions relate to parameters, which parameters are required for each action, or what the tool returns. This is insufficient for an agent to correctly select and invoke actions.

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%, so all 19 parameters are already documented in the schema. The description adds no parameter-specific detail; it only loosely aligns 'versioning, change tracking, conflicts' with some actions. This meets the baseline for schema-driven parameter understanding.

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 states 'Manage storage operations' which identifies the domain but is vague about specific actions. It lists categories like versioning, change tracking, conflicts, and integrations, but does not provide a specific verb+resource or distinguish among the nine actions in the schema. It is somewhat differentiated from sibling tools that focus on templates and PRPs, but the purpose is still generic.

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 vs alternatives. The description does not mention any exclusion criteria, alternative tools, or specific use cases for the various actions. This leaves the agent to infer usage from the schema 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 carries the full burden of behavioral disclosure. It only says 'Search', which suggests a read-only operation, but it does not disclose return format, case sensitivity, pagination, or any potential side effects. This lack of behavioral detail 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?

The description is a single concise sentence that front-loads the action and resource. It uses no unnecessary words and is easy to parse, making it appropriately sized for this simple search tool.

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 is a simple search with two parameters and no output schema or annotations, the description provides the minimum viable information. However, it lacks context about result format, search behavior nuances, or integration with sibling tools, leaving it somewhat incomplete for an agent to fully understand what to expect.

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 provides descriptions for both parameters (query and category), achieving 100% coverage. The description adds value by clarifying that the query searches across name, description, or tags, which goes beyond the schema's generic 'Search query string'. However, the category parameter remains only 'Optional category filter' with no further elaboration.

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 action ('Search') and target ('templates'), and specifies that search can be performed by name, description, or tags. This distinguishes it from the sibling tool 'list_templates', which likely returns all templates without a search query.

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 when searching for templates by name, description, or tags, but it does not explicitly state when to use this tool versus alternatives like list_templates. There are no 'when not to use' statements or reference to other tools, so guidance is only implied.

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 behavior. It mentions change tracking and Archon sync but does not explain that this is a mutation operation, whether backups are created by default, or whether changes are reversible. The safety profile is unclear.

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 is front-loaded with the action and key differentiators. It includes 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?

Despite having 9 parameters, no output schema, and no annotations, the description is minimal. It fails to clarify whether updates are partial or full, default behavior for backups, or what is returned. Significant gaps remain for a tool of this complexity.

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 all 9 parameters with descriptions, so high coverage gives a baseline of 3. The description adds context around change tracking and Archon sync but does not materially expand on parameter meanings beyond what the schema already states.

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 updates an existing PRP and highlights distinctive features (change tracking and Archon synchronization). This distinguishes it from siblings like generate_prp and validate_prp.

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?

Usage is implied by the action 'update existing PRP' but there is no explicit guidance on when to choose this over alternatives, nor exclusions. Sibling tools are contextually different, but no elaboration is 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 full responsibility for behavioral disclosure. It doesn't mention whether this is a read-only operation, what the output looks like, whether it modifies anything, or what happens on validation failure. This is a significant transparency gap for a tool that likely returns a validation report.

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 with no fluff. It could be slightly longer to add behavioral context, but as far as conciseness, every word earns its place. Four is appropriate because it is effective yet minimal.

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 no output schema, no annotations, and a terse description. It doesn't explain what validation entails, what the return value looks like, or how to interpret results. For a validation tool that likely produces a structured report, this is under-specified. The sibling tools don't provide enough contextual clues to compensate.

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%, with both parameters clearly described in the schema. The description adds no parameter-level detail, but that's acceptable given the schema fully documents the inputs. 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 action (validate) and the resource (PRP) against a specific criterion (context engineering best practices). It's specific enough, though 'PRP' is an acronym that isn't expanded for a new user. It doesn't need to distinguish from siblings since no other validate tool exists.

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 guidance on when to use this tool versus alternatives like analyze_context or generate_prp. It doesn't state prerequisites, expected input format, or what to do with validation results. A user must infer usage from the name alone.

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