flowzap

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

With no annotations provided, the description bears the full burden of disclosing behavioral traits. It states the tool applies patches but does not disclose potential side effects, such as whether the operation is destructive (e.g., overwriting the input code) or whether it requires specific prerequisites like valid syntax. Since it mutates code, it should explain what happens to the original code, but it doesn't.

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, which is concise, but it lacks crucial detail that would make it more effective. It front-loads the primary purpose but omits usage context or behavioral notes. It earns a middle score because it is succinct but not comprehensive.

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

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

Given the complexity of a tool that applies patch operations, the description is incomplete. It does not explain the expected format of operations (e.g., how to specify node vs edge updates), nor does it describe the return value or what happens on success/failure. Without an output schema and with only minimal input schema details, an agent has insufficient information to correctly construct a call. It is deficient for a tool of this nature.

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%, but the schema is minimal: 'code' is described as 'Current FlowZap Code' and 'operations' as 'Array of patch operations'. The description adds the types of operations (insert/remove/update nodes or edges), which clarifies 'operations', but it doesn't explain the structure of each operation or how 'code' is used (e.g., is it modified in place?). Since the schema is thin, the description provides some value but not enough to compensate for the lack of detail on operation format.

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 the tool applies structured patch operations (insert/remove/update nodes or edges) to FlowZap Code, which is a specific verb and resource. However, it doesn't clearly distinguish between 'apply_change' and sibling tools like 'flowzap_diff' or 'flowzap_fix', which might have overlapping purposes. The description is clear but not fully differentiated from potential siblings.

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

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

There is no explicit guidance on when to use this tool versus alternatives. It doesn't mention when not to use it, nor does it reference any sibling tools. The description implies that it is for applying changes, but without context on how it compares to other FlowZap tools (e.g., 'flowzap_fix' might also modify code), an agent lacks direction 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It says 'Convert' but does not clarify whether the operation is read-only, whether it persists or returns a diagram, or whether it has side effects on the source content. The behavioral surface is largely opaque.

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 with no filler. It front-loads the action and includes the key artifact types, making it easy for an agent to scan and understand the tool's 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?

There is no output schema and no annotation coverage, so the description should explain what the agent can expect after conversion. It does not mention the return value, output format, or any constraints on content size or format. The description is adequate for basic awareness but incomplete for fully informed 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 67%, and the description adds some meaning by mapping artifact types to the artifactType enum values. However, it does not explain the expected format of the 'content' field for each artifactType, nor does it expand on how 'view' affects the output beyond the schema's enum values.

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 'Convert' and identifies the resource: HTTP logs, OpenAPI specs, or code snippets become a FlowZap diagram. It is clear about the input-to-output transformation, though it does not explicitly contrast itself with the similar-sounding flowzap_export_graph sibling.

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 context is implied: use this when you have one of the listed artifact types and want a diagram. However, it does not state when to prefer this over siblings like flowzap_export_graph or flowzap_validate, nor does it mention any conditions where it should not be used.

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 discloses that the analysis is powered by Deepseek in China, that it is an advisory review rather than legal advice, and that it returns a Markdown summary per detectable framework. It also mentions the free quota, which is useful operational context. It does not fully describe data-handling implications beyond the processor disclosure, but it is substantially 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 longer than average, but most sentences carry useful context: output format, quota, manual alternative, processor disclosure, and legal disclaimer. The main purpose is front-loaded. Some content (legal subprocessor link) could arguably live elsewhere, but for a compliance tool it is relevant and appropriately placed.

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?

There is no output schema, yet the description explains exactly what the agent should expect: a Markdown summary with control, status, detail, and recommendation for each detectable framework. It also covers scope limits (only detectable elements), quota, manual fallback, third-party processing, and advisory nature. This is complete enough 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?

Schema description coverage for the parameters is 100%, so the schema already documents 'code' and 'lng' clearly. The description does not add further meaning about the language enum or code format; it only mentions 'FlowZap Code' in passing. This meets the baseline but does not elevate it.

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 starts with a specific action ('Run an automated compliance review'), names the exact frameworks (SOC2, GDPR, PIPL, EU AI Act), and identifies the resource being reviewed (a FlowZap Code data flow). It also states the return format, making it easy to distinguish from siblings like flowzap_validate or flowzap_fix, which serve different purposes.

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

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

The description makes clear that this tool is for automated architectural compliance reviews of FlowZap Code. It also provides an explicit alternative for a different situation: if users need unlimited manual reviews, they should use the linked web checker. It does not explicitly exclude use when other sibling tools (e.g., flowzap_validate) would be more appropriate, but the usage context is reasonably 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 carries the full burden of behavioral disclosure. It discloses that the result is a shareable URL, but does not state whether creating the playground has side effects, whether it requires authentication, whether the URL is persistent, or what happens if the code is invalid.

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 short and front-loaded, with the core purpose in the first sentence. The second sentence adds view guidance, though it is somewhat vague; overall, there is no redundant text.

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 that no output schema exists and no annotations are present, the description should explain more about the expected behavior, return format, and when to use this tool. It mentions the output is a shareable URL but omits side effects, prerequisites, and selection criteria relative to sibling tools.

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 the baseline is 3. The description adds a slight hint that the view parameter can be set to 'architecture', 'sequence', or 'mindmap' when appropriate, but this is too vague to meaningfully expand on the schema's own parameter descriptions.

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 a specific verb and resource: 'Create a shareable FlowZap playground URL.' This clearly identifies the tool's function and distinguishes it from sibling tools like flowzap_validate or flowzap_export_graph, none of which involve creating a playground URL.

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 given for when to use this tool versus the sibling alternatives such as flowzap_export_graph, flowzap_diff, or flowzap_validate. The only usage hint is 'Set view to ... when appropriate,' which is vague and does not explain when a particular view should be selected.

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?

There are no annotations, so the description carries the full burden. It clearly states the operation is a comparison (read-only), which is a key behavior. However, it does not disclose details like whether the diff is side-by-side, or if it is safe to run without side effects. Since it explicitly mentions 'returns a structured diff', it adds behavioral context, but it lacks depth. Thus, a 3 is appropriate.

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 is front-loaded with the primary action ('Compare') and the resource. There is zero waste and every word earns its place. It is appropriately sized for the tool's 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?

Given the tool is a simple comparison with two parameters and no output schema, the description is mostly complete. It does not explain the format of the return value beyond 'structured diff', but for a diff tool, this is likely sufficient. With no output schema, adding more detail about the return format would be helpful, but the current description meets the basic needs.

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 the schema describes both parameters ('oldCode' and 'newCode') as 'Original FlowZap Code' and 'Updated FlowZap Code'. The description adds minimal semantic value by implying the diff is between old and new, which is already clear from the parameter names and schema. With high schema coverage, baseline 3 is correct.

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 a specific verb ('Compare') and resource ('two FlowZap Code versions') and mentions the output ('structured diff'). It is clear what the tool does, but it does not differentiate from siblings like flowzap_validate or flowzap_fix, which might also compare or analyze code. It is not a tautology, so it earns a 4.

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 when to use this tool: when you need to compare two versions of FlowZap Code and get a diff. However, it does not explicitly state when not to use it or mention alternatives such as flowzap_validate for validation or flowzap_apply_change for applying changes. The usage context is clear but exclusions are missing, so it gets a 3.

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 state the primary behavior: parsing code into a graph with lanes, nodes, and edges. However, it does not disclose error handling for invalid code, whether the graph follows a specific schema, or any limitations on input size or format.

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 front-loads the action and output shape without redundant words. It conveys the essential information efficiently for a simple one-parameter 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?

For a low-complexity tool with one parameter and no output schema, the description provides enough high-level information: input is code, output is a structured JSON graph with lanes, nodes, and edges. It stops short of detailing the exact graph schema or failure behavior, but the omission is minor given the tool's simplicity.

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 the only parameter, 'code', is already described in the schema as 'FlowZap Code to parse'. The description adds little beyond confirming the input is FlowZap code, 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 uses a specific verb ('Parse') with a clear resource ('FlowZap Code') and a concrete output ('structured JSON graph (lanes, nodes, edges)'). This distinguishes it from siblings like flowzap_validate or flowzap_get_syntax by stating exactly what it produces.

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 instead of siblings such as flowzap_artifact_to_diagram or flowzap_validate. There is no mention of context, prerequisites, or exclusions, so an agent must infer the appropriate use case.

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 behavioral burden and does so well: it states determinism, discloses that the return value includes repaired code plus a list of corrections, and explains how unrepaired errors are handled. Minor unspecified traits like whether input is mutated are not addressed, but the core behavioral contract is 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 two dense sentences with no filler. The action and supported error types are front-loaded, and the second sentence adds meaningful behavioral constraints 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?

Despite having no output schema, the description explains what is returned and how edge cases (unrepairable errors) are handled. The only required parameter is documented in the schema, so an agent has everything needed to invoke the tool correctly.

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

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

Schema description coverage is 100%, so both parameters are already documented in the schema. The description adds no parameter-level detail beyond that, which is acceptable but not above 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 uses a specific verb ('repair') and identifies the exact resource ('FlowZap Code errors'), then enumerates the concrete error categories it handles. The list makes it distinguishable from sibling tools like flowzap_validate and flowzap_apply_change.

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 intended use case is clear: this tool is for mechanical, deterministic repairs of FlowZap Code errors. It does not explicitly name alternative tools or give when-not-to-use guidance, but the deterministic scope and the 'never invents content' constraint provide clear routing 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 carries the full burden, and it does indicate the tool returns documentation and examples. However, it does not explicitly state that the operation is read-only or describe any behavioral details such as output format or error behavior.

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

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

The description is one short, front-loaded sentence with no wasted words. It is appropriately concise, though it sacrifices useful usage context that could be added without much bloat.

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 zero-parameter tool the description is minimally complete, but there is no output schema and no detail about what the returned documentation/examples look like. An agent would need to infer the exact return format.

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 tool has zero parameters and schema coverage is 100%, so there is nothing for the description to add about parameter meaning. Per the zero-parameter baseline, this is handled adequately.

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 names a specific action ('Get') and a specific resource ('FlowZap Code syntax documentation and examples'), making the tool's basic purpose clear. It is distinguishable from siblings by topic, though it does not explicitly contrast with any sibling 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?

There is no guidance about when to use this tool versus alternatives such as flowzap_validate or flowzap_fix. The description implies it is for syntax reference, but it never states a selecting condition or excludes other 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 and does so exceptionally well. It discloses the structured verdict format, the specific blocking/advisory/info classification rules, the rendering limitations that trigger each level, and the fact that parsing is local with no API call. This gives an agent a reliable behavioral model.

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 dense but every sentence earns its place: main purpose, return structure, classification rules, and an important behavioral guarantee. It is front-loaded with the core purpose and avoids filler 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?

The tool has one parameter, no output schema, and no annotations, yet the description explains what the returned verdict will contain and what conditions trigger each outcome. An agent has enough context to call the tool and interpret its result without ambiguity.

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 'code' parameter, and the schema already documents it as FlowZap Code to inspect. The description adds context about local parsing and Mind Map readiness, but it does not need to add much more given the high coverage and simple parameter shape.

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 a specific operation—checking FlowZap Code for suitability to Mind Map rendering—and clearly distinguishes this from a general validation or mutation tool by describing the verdict output and rendering-specific rules. It is not a tautology and the resource and intent are immediately clear.

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 establishes the context for use: checking whether already-valid FlowZap Code is Mind Map-ready, and it explains the outcome categories. It does not explicitly name alternative sibling tools or state when not to use this tool, so it stops short of full when-to-use versus alternative 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 provided, the description carries the full burden. It discloses that it 'Validates the code first' and 'creates a shareable URL,' which is useful behavioral context. However, it does not mention what happens if validation fails, whether the URL expires, or any side effects. It is not misleading but leaves some behavioral aspects unspecified.

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 concise sentences, front-loaded with the main purpose, followed by behavioral details and a usage guideline. There is no padding, and every sentence earns its place. It is efficient and well-structured.

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, no output schema, and no annotations, the description covers the essentials: what it does, how it behaves (validation), and the output (shareable URL). It also states a precondition. Minor gaps remain, such as the exact return structure or error handling, but these are less critical given the tool's simplicity.

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% (the single 'code' parameter has a description), so the baseline is 3. The description adds meaning by stating that the code must be validated and approved, implying that the code must be in a valid, approved state before use. This goes beyond the schema's simple 'FlowZap Code to load' and adds semantic context about the expected input quality.

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 a specific verb ('Create') and a specific resource ('FlowZap playground session') with a distinguishing feature ('opens directly in Mind Map view (?view=mindmap)'). It differentiates from sibling flowzap_create_playground by specifying the view, and also notes the validation step. This is clear, specific, and non-tautological.

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 'Use this after flowzap_mindmap_validate and flowzap_mindmap_approve have passed,' providing a clear precondition for when to call this tool. It does not explicitly contrast with sibling flowzap_create_playground or state when not to use it, but the precondition and view-specific behavior give enough context for an agent to select correctly.

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 carry behavioral disclosure on its own. It does disclose the returned structure (tree with root, branches, cross-links), but it does not clarify whether this operation is read-only, whether it persists anything, or what the generated code skeleton actually looks like. This leaves some behavioral ambiguity for an agent.

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 short, purposeful sentences: what it generates, what it returns, and when to use it. It is front-loaded and contains no filler or repetition of schema 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 no output schema, the description provides a useful high-level return shape. It also communicates the bootstrap purpose and relies on the schema for parameter details. It could be more complete by stating the output format or how cross-links are enabled, but the core context needed to invoke the tool is present.

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 the input schema fully documents depth, topic, and branches with defaults and constraints. The description adds no extra parameter meaning beyond mentioning branches in its structural explanation, which keeps it at the 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?

The description begins with a specific verb and resource: 'Generate a ready-to-extend FlowZap Code skeleton for a Mind Map.' It further differentiates the tool by describing the output shape (central circle root, rectangle branches/sub-branches, optional cross-links), making it distinct from validation or approval sibling tools.

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

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

The description explicitly says 'Use this to bootstrap a new mind map,' which gives a clear when-to-use directive. It does not explicitly name alternatives or state when not to use it, but the bootstrap framing is enough to route an agent away from validate/approve/artifact conversion 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 behavioral burden and does well by enumerating exactly what is checked: syntax validity, no diamonds, no taskboxes, root circle, and branch rectangles. It implies a non-mutating validation operation and gives the agent concrete expectations, though it does not describe the success/error response format.

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

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

Two focused sentences, with the primary purpose front-loaded and the validation criteria compactly listed. Every sentence adds value, with no filler or repetition of schema 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 one-parameter validation tool, the description provides sufficient context: the exact validation rules and the recommended position in the workflow. The only notable gap is the lack of information about the tool's return value, but the tool's simplicity and clear purpose keep this from being a major omission.

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%, and the single 'code' parameter is already well-described in the schema. The description does not add parameter-level detail such as formatting or examples, 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?

States a specific verb ('Validate'), resource ('FlowZap Code'), and scope ('specifically for Mind Map diagrams'). It lists concrete validation criteria, and distinguishes itself from the generic sibling flowzap_validate by narrowing to mind map readiness.

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 directs the agent to use this tool before flowzap_mindmap_approve and flowzap_mindmap_create_playground, establishing clear workflow sequencing. The phrase 'specifically for Mind Map diagrams' communicates when this variant is preferred over the general validator.

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 behavioral burden. It does disclose the return behavior ('errors and stats'), but it does not explicitly state side-effect-freedom, permissions, or how the lng parameter affects messages. The verb 'validate' strongly implies a read-only operation, which partially compensates.

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 with no filler. The core action is front-loaded and the return information is presented immediately and economically.

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 low-complexity validation tool with fully documented parameters, the description covers the operation and broad return shape. It stops short of defining what 'stats' contains or how lng alters messages, but these are minor gaps given the schema's parameter documentation.

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 both `code` and `lng` already described in the input schema. The description adds no parameter-level detail, which is acceptable because the schema carries the full meaning.

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?

States a specific verb ('Validate'), a specific resource ('FlowZap Code syntax'), and the return shape ('errors and stats'). This clearly differentiates it from siblings like flowzap_fix (fixing) and flowzap_get_syntax (retrieving syntax).

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 but gives no explicit when-to-use guidance or exclusions. It does not mention alternatives such as flowzap_fix or flowzap_compliance_check, so an agent has no basis for choosing this tool over similar siblings.

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