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 mentions 'within timeout' but does not explain whether the tool polls, fails immediately, requires the element to exist, or what happens on timeout. This is minimal for a tool meant to gate test validity.

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 front-loaded sentence with no filler words. It is concise, though it sacrifices necessary behavioral detail for brevity.

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 four parameters, a nested locator object, no output schema, and no annotations, this description is too thin. An agent cannot infer the full calling contract, failure semantics, or default timeout behavior from it.

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%, and the description only loosely references 'locator' and 'timeout.' It does not explain sessionId, serverUrl, the nested locator structure, whether timeoutMs is optional, or how the strategy/value pair is interpreted.

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 ('assert'), resource ('a locator'), and negation ('not visible') with a timeout scope. The 'not visible' phrasing clearly differentiates it from siblings such as appium.assert_visible and appium.wait_for_visible.

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 on when to use this versus assert_visible or wait_for_visible. The description conveys only what the tool does, not the conditions that should lead an agent to choose it over alternatives.

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 behavioral burden. It usefully discloses that a non-visible element yields false rather than an exception. However, it omits whether it waits during timeoutMs, what it returns on success, and any failure/error behavior, leaving key traits unexplained.

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, front-loaded, and each sentence serves a purpose. It loses one point because 'Returns passed false' is awkwardly phrased and may confuse an agent into thinking a field named 'passed' is returned rather than simply 'false'.

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 annotations, no output schema, and four parameters, the core assertion behavior and the false-on-failure contract are present. Yet timeout semantics, the success return value, and the role of optional parameters are missing, leaving meaningful gaps in what an agent needs to invoke it confidently.

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

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

The input schema has 0% description coverage, so the description needed to compensate, but it only refers generically to 'a locator'. It adds no meaning for sessionId, serverUrl, timeoutMs, or how locator strategies behave, making it hard for an agent to construct a correct call.

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 first sentence names a concrete operation and target: assert visibility of a locator. The second sentence adds that it returns false instead of throwing, which helps distinguish it from tools like appium.assert_not_visible and appium.wait_for_visible. However, it never explicitly names a sibling or state the alternative condition.

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 word 'Assert' plus the non-throwing return behavior implies this is for a boolean visibility check, but there is no explicit guidance on when to use this vs. waiting or negating. In particular, it does not point to appium.wait_for_visible for polling scenarios or appium.assert_not_visible for the inverse check.

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

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

No annotations are provided, so the description carries the full burden. It explicitly includes bracketed risk signals: '[approval required][device mutation][risk:dangerous]', which disclose approval needs, device-state mutation, and danger. It lacks detail on session cleanup or resource lifetime, but the key safety traits are surfaced.

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 risk flags are front-loaded, and every clause adds distinct value: what the tool does and what input shape it expects.

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 is adequate for a simple creation tool, and the risk flags cover approval and danger. But it omits the optional 'serverUrl' semantics, does not describe what the response returns (e.g., sessionId), and never mentions that the session should later be cleaned up with appium.delete_session. These are meaningful gaps given there is no output 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 description adds real meaning for the 'capabilities' parameter by explaining it accepts W3C capabilities or a raw capabilities object, which is more than the schema's bare object type. However, 'serverUrl' is not mentioned in the description, and schema description coverage is 0%, so that parameter's semantics depend entirely on its self-explanatory name.

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 an Appium session.' It also clarifies the input form ('W3C capabilities or raw capabilities object'), which distinguishes it from session teardown tools like appium.delete_session. This is unambiguous and differentiating.

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

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

The description explains how to call the tool ('Pass W3C capabilities or raw capabilities object') but gives no guidance on when to use it, prerequisites such as an Appium server or device, or how it relates to alternatives like appium.delete_session or env.ensure_appium. An agent must infer the appropriate 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 structured annotations are present, so the description carries the behavioral burden. It includes '[approval required][device mutation][risk:dangerous]', which communicates risk and destructive intent. However, it does not disclose the full behavioral consequences of deleting a session, such as what happens to the device under test or whether the session ID becomes 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 a single short, front-loaded sentence with no filler text, and the warning tags are placed at the front. It is appropriately concise for a tool of this apparent 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?

For a destructive lifecycle operation, this is thin context. It omits prerequisites or teardown usage, does not describe the effect on the device or Appium server, and provides no guidance about what to do after deletion. The lack of an output schema further raises the burden on the description to fill in these gaps.

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% and the description adds no information about sessionId or serverUrl. The agent must infer parameter semantics solely from the parameter names, and the description does not compensate for the missing schema documentation.

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 action ('Delete an Appium session') clearly, identifying a specific verb and resource. It stops short of a 5 because it largely restates the tool name and does not add any scope or distinguishing details relative to sibling Appium lifecycle 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?

There is no guidance about when this tool should be used, when it is unnecessary, or how it fits into a teardown flow versus other session-related tools. The warning tags signal caution but provide no decision criteria for an agent choosing whether to invoke this tool.

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 states what the tool returns but not whether it requires an active Appium session, how it handles errors, whether it reads current UI state, or what 'compact' means in terms of output size or structure. The description adds only a minimal parsing nuance beyond the purpose 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 a single sentence, front-loads the core behavior with 'Return a compact accessibility summary', and contains no filler or redundant content. It earns its place without 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?

The tool has no output schema, no annotations, and undocumented parameters, so the description needs to supply substantial context. It does not define what the accessibility summary contains, how it relates to get_page_source, whether it can be used for assertions, or what the return structure looks like. An agent would likely need to inspect other tools or experiment to use it 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 0%, so the description must compensate by explaining serverUrl and sessionId. It does not mention either parameter at all. An agent has no guidance on what serverUrl is for, whether sessionId is a session identifier from appium.create_session, or how the parameters relate to fetching and parsing page source.

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 ('Return') and a concrete resource ('compact accessibility summary parsed from page source'), making the core function clear. It implies a distinction from appium.get_page_source (raw page source vs. parsed summary) but does not explicitly differentiate itself from other accessibility-related siblings like appium.assert_accessibility_labels.

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 about when to use this tool versus alternatives such as appium.get_page_source, appium.observe_screen, or appium.assert_accessibility_labels. The phrase 'parsed from page source' hints at a relationship to get_page_source, but there is no explicit when-to-use, when-not-to-use, or prerequisite 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 of behavioral disclosure. It only states the output is raw XML, but does not mention potential errors, session requirements, or that the output may be large. It is a simple read operation but lacks any caveats or context.

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

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

The description is a single, efficient sentence that immediately states the core function. No fluff or unnecessary detail; it is 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?

For a tool with two parameters and no output schema or annotations, the description is inadequate. It fails to explain the parameters, the structure of the XML returned, or when to use this tool over alternatives. An agent would likely struggle to invoke it correctly without additional context.

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%, and the description does not explain what serverUrl or sessionId mean. The agent cannot infer the purpose of these parameters from the description alone, making it impossible to correctly populate them without external knowledge.

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 ('Return') and the specific resource ('raw Appium page source XML'). It distinguishes itself from siblings like appium.observe_screen and appium.get_accessibility_tree by focusing on the raw XML output.

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 on when to use this tool versus the many Appium sibling tools. The description does not mention alternatives or conditions for selection, leaving the agent to infer from the name and description.

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. It does disclose safety-relevant traits via '[approval required][device mutation][risk:dangerous]', which is valuable, but it doesn't explain what state changes occur (e.g., whether it can exit the app, lose unsaved work, or fail without a back stack). Partial disclosure.

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, compact sentence with risk tags front-loaded. There is no fluff, and the essential warning is prominent. It could include more context, but for what it says, it is efficient.

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

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

Given no annotations and no output schema, the description leaves significant gaps: no return value, no failure modes, no prerequisites, and no guidance on when navigation is appropriate. It is a minimal statement of action and risk, insufficient for confident autonomous 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 description coverage is 0%, so the description must compensate. It mentions neither serverUrl nor sessionId, leaving their purposes undocumented. The parameter names are somewhat self-explanatory, but the description adds no meaning beyond the schema.

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

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

The description names a specific action (send back navigation) on a specific resource (Android/iOS Appium session), making it clearly distinct from sibling tools like appium.tap_by_text or appium.swipe. It doesn't explicitly name alternatives, so it falls short of a 5.

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 on when to use this tool versus the many other navigation or verification tools, no mention of prerequisites like having an active session, and no exclusions. Usage is only implied by the tool name.

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 mentions 'optionally waiting for app UI readiness' but does not explain what that entails, how long it might block, or any side effects. It also fails to mention that the tool may take significant time due to waiting, or what 'readiness' means in terms of parameters like stableMs or waitForAnyText.

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 and front-loaded with the core action. However, it is so brief that it omits essential details about parameters and behavior, making it under-specified rather than efficiently 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?

For a tool with 8 undocumented parameters and no output schema, the description is grossly incomplete. It does not explain what the screenshot and page source return, how the waiting behavior is controlled, or any of the parameter semantics. An agent cannot reliably use this tool based on the given information.

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 has 0% description coverage, so the description must compensate by explaining parameter meanings. It does not mention any of the 8 parameters (prefix, stableMs, minWaitMs, serverUrl, timeoutMs, waitForAnyText, waitForPackageIdle) at all. Agents have no way to know what these parameters control, making correct invocation impossible.

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 captures a screenshot and page source for the current Appium session, and optionally waits for UI readiness. This is a specific verb+resource combination. However, it does not explicitly differentiate itself from siblings like appium.get_page_source or device.capture_screenshot, though the combination and the waiting aspect make it distinct.

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. There is no mention of when to prefer this over calling appium.get_page_source and device.capture_screenshot separately, or when the waiting feature is necessary. The description implies usage but gives no explicit context or exclusions.

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

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

With no annotations present, the description carries the full burden. It includes explicit tags '[approval required][device mutation][risk:dangerous]', which disclose safety and mutation traits. However, it does not explain side effects like screen state changes, reversibility, or session requirements, so it only partially covers behavioral transparency.

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

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

The description is extremely concise and front-loaded with risk tags, but it is under-specified rather than efficiently sized. It contains no wasted words but lacks critical content, so it does not earn a higher score.

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 7 parameters, zero schema coverage, no annotations, and no output schema, the description is severely incomplete. An agent would not know the coordinate system, required session setup, optional duration semantics, or expected effect, making correct invocation highly uncertain.

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% and the description fails to explain any of the 7 parameters. It merely says 'by coordinates', leaving startX/startY/endX/endY units and coordinate space unspecified, and durationMs, serverUrl, and sessionId entirely unexplained. The description adds almost no meaning beyond the bare 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 states a specific verb ('swipe') and resource ('touch by coordinates'), clearly identifying the action. However, it does not differentiate from sibling tools like appium.tap_coordinates, so it misses the explicit sibling contrast that would make it a 5.

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 tap_coordinates or other gestures. The sole sentence implies usage ('swipe') but gives no context on prerequisites, scenarios, or exclusions.

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

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

Annotations are absent, so the description must carry the burden. It does disclose 'approval required', 'device mutation', and 'risk:dangerous', which are important behavioral warnings. However, it does not describe error handling, session requirements, or side effects beyond the mutation, leaving a significant portion of behavior undisclosed.

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

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

The description is extremely concise, consisting of a single sentence plus risk tags. It wastes no words and is front-loaded with the risk warnings. However, it may be too minimal to convey necessary nuance, though it earns a high score for efficiency.

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 several sibling tap methods, the description is incomplete. It does not explain when to prefer this over tap_by_text or tap_by_resource_id, nor does it mention that an active session is required (though the schema indicates it). Error behavior and post-conditions are absent, making it insufficient for an agent to confidently select and invoke the 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 description coverage is 0%, and the description adds no parameter-specific meaning. It does not explain that sessionId is required, what serverUrl is for, or what format accessibilityId should be. The parameter names are somewhat self-explanatory, but the description does not compensate for the missing schema documentation.

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

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

The description clearly states the verb 'tap' and the resource 'accessibility id', so the purpose is unambiguous. However, it does not differentiate from sibling tools like tap_by_text or tap_by_resource_id, which weakens its clarity in context.

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 on when to use this tool over alternatives. It does not mention that it should be chosen when an accessibility ID is available, nor does it exclude cases where text or resource ID would be more appropriate. The description gives no context for selection.

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

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

The bracketed tags '[approval required][device mutation][risk:dangerous]' are likely part of the description but act as annotations. However, the description adds little beyond these tags: no details on side effects, permissions, or error conditions. With no annotations present, the description fails to disclose behavioral traits beyond the mutation risk.

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, concise and gets to the point. It includes the necessary context for the resource id parameter. No wasted words.

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 mutation tool with dangerous risk, the description lacks guidance on preconditions (e.g., app must be launched), error scenarios, or behavioral details. It also doesn't explain the 'serverUrl' parameter or how session is used. Incomplete for safe and correct usage.

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%, so the description must compensate. It only explains 'resourceId' (Android resource id or Appium id locator), but leaves 'serverUrl' and 'sessionId' entirely undocumented. The description adds minimal value for the parameters.

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 (tap) and the target (by Android resource id or Appium id locator). It distinguishes from sibling tools like appium.tap_by_text and appium.tap_coordinates by specifying the locator type.

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

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

The description implies usage for Android UI automation, but does not explicitly state when to use this tool versus alternatives like tap_by_accessibility_id or tap_by_text. No exclusions or alternative routing 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?

Although no annotations are provided, the description includes safety tags '[approval required][device mutation][risk:dangerous]' and discloses the matching fallback strategy. This provides meaningful behavioral context beyond what a schema would show, though it omits details like failure behavior and waiting.

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 with the most critical safety information front-loaded in tags. It is concise, non-redundant, and earns its place without verbosity.

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 mutation tool with 5 parameters and no output schema, the description covers the core purpose and matching logic, but leaves out details about timeout behavior, matchMode values, and what happens if no element is found. This is adequate but not complete for a dangerous operation.

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%, so the description must explain parameters. It only explains 'text' implicitly and hints at matching behavior, but does not clarify 'matchMode', 'timeoutMs', 'serverUrl', or 'sessionId'. The description adds minimal value for the other three optional parameters.

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 explicitly states the verb 'Tap', the resource 'visible element by text', and the behavior 'exact-first matching before contains fallback'. This clearly differentiates it from sibling tools like tap_by_accessibility_id and tap_by_resource_id, which use different locators.

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 this tool is for tapping elements identified by text, but it does not explicitly mention when to prefer it over alternatives or when not to use it. Sibling tools exist for different locators, but no guidance is given on selection 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?

The description includes inline tags '[approval required][device mutation][risk:dangerous]' which disclose that this is a dangerous, mutating operation requiring approval. However, these tags are not formal annotations, and the description does not explain what 'dangerous' means in practice (e.g., could tap unintended UI elements, cause navigation, or trigger irreversible actions). It also doesn't mention that coordinates are relative to the device screen and may vary by resolution. The tags add some transparency, but the description could go further.

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 plus a short constraint, which is concise and front-loaded. The inline tags add useful context without bloating the text. It loses one point because the parameter semantics gap means the description is too short to be fully self-sufficient.

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 dangerous mutation tool with no annotations, no output schema, and 0% schema coverage, the description is incomplete. An agent needs to know the coordinate system, units, and potential side effects to use this safely. The sibling list shows many semantic alternatives, and the description correctly routes away from them, but it doesn't provide enough operational detail for a tool that could cause harmful taps.

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%, so the description must compensate for the schema's lack of parameter documentation. The description only mentions 'screen coordinates' but does not explain that x and y are pixel coordinates, what coordinate system is used (e.g., top-left origin), or what serverUrl and sessionId are for. With 4 parameters and zero schema coverage, this is a significant gap.

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 ('Tap screen coordinates') and adds a clear constraint ('Use only when semantic locators are unavailable'). It distinguishes this from sibling tools like appium.tap_by_text, appium.tap_by_accessibility_id, and appium.tap_by_resource_id, which are semantic locator-based alternatives. It could be slightly clearer that this is a raw coordinate tap on the Appium session, but the core purpose is unambiguous.

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

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

The description explicitly says 'Use only when semantic locators are unavailable,' which is a direct usage guideline. It implies that semantic locator tools (tap_by_text, tap_by_accessibility_id, tap_by_resource_id) should be preferred, and this tool is a fallback. This is strong guidance for an agent deciding between siblings.

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 does include the pre-tags '[approval required][device mutation][risk:dangerous]' which add context, but it does not explain the device mutation effect, whether it clears the field first by default, whether text is appended or replaced, or what happens on failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

The description is one sentence with useful pre-tags, but it is not front-loaded with the most decision-relevant info and spends precious space listing locator strategies that are already in the schema. It is adequately short but omits important behavioral details that could have been added without much length.

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

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

The tool mutates a device and has six parameters with no schema descriptions and no output schema. The description does not cover return behavior, preconditions like an active Appium session or visible element, or the effect of `clearFirst`. Given the tool's complexity and risk level, the description is not complete enough for an agent to invoke it safely and 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?

The input schema has 0% description coverage across 6 parameters, so the description must compensate heavily, but it only mentions locator strategies and 'text' implicitly. It does not explain the `mode`, `clearFirst`, `serverUrl`, or `sessionId` parameters, nor does it clarify the structure of the `locator` object beyond listing strategies. The description adds almost no meaning beyond the parameter names and 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 clearly states the action ('Type text into an element') and specifies the supported locator strategies, which helps distinguish it from tap-focused siblings like appium.tap_by_text and appium.tap_by_accessibility_id. However, it doesn't explicitly name a sibling or contrast itself with alternative tools, so it falls short of full differentiation.

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 on when to use this tool versus alternatives such as tap_by_text or tap_coordinates, nor any mention of prerequisites like needing an active session or a visible element. The usage context is implied by the verb 'type', but the description does not help an agent decide between this and other input methods.

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

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

No annotations provided, so the description must carry behavioral transparency. It only says 'wait until visible' but doesn't disclose timeout behavior, polling interval, what happens on timeout (throws exception?), or whether it returns anything. This is insufficient for a wait operation.

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

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

The description is a single short sentence, which is concise and front-loaded. However, it's so brief that it sacrifices necessary detail. It earns high marks for conciseness but at the cost of completeness.

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 4 parameters and no output schema, this description is incomplete. An agent doesn't know what happens if the element never becomes visible, how long to wait by default, or what the return value indicates. The sibling tools suggest a testing context, but the description doesn't provide sufficient context 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 has 0% description coverage, so the description must explain parameters. It doesn't mention timeoutMs, serverUrl, or the locator structure. The agent only gets the schema enum for strategy, but no semantics for timeout. The description adds no parameter 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?

The description clearly states the tool's function: waiting for a locator to become visible. It uses a specific verb 'wait' and identifies the resource (locator visibility). It distinguishes from siblings like appium.assert_visible which likely check visibility immediately, but doesn't explicitly contrast 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?

No guidance on when to use this tool versus alternatives. It doesn't mention that this is for waiting before actions, or that assert_visible is for immediate checks. The agent must infer usage from the name and siblings.

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 disclose important behavioral traits through inline tags: '[approval required][workspace write][network][risk:dangerous]'. It also states the return behavior (returns artifact paths), which goes beyond what the name alone conveys. However, it does not elaborate on what the write entails or why it is dangerous, so it is not a 5.

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, front-loaded with risk and permission tags, and efficiently states the action and return value. It is appropriately sized for a simple build tool, though it omits important usage and parameter details that would warrant a 5.

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 one optional parameter, no output schema, and no annotations, the description adequately covers the primary purpose and return type. However, it lacks context about prerequisites (e.g., needing a project set up), the meaning of the 'kind' parameter, and any error or fallback behavior when no APK is found, so it is not fully 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?

The schema has one optional parameter 'kind' with enum values (flutter, react-native, android) and 0% schema description coverage. The description does not add any meaning about this parameter – it does not explain what each value does, whether the parameter is needed, or what happens if omitted. Since schema coverage is 0%, the description must compensate but fails to do so, leaving the 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 states a specific verb ('Build') and resource ('debug APK') and explicitly says it returns discovered APK artifact paths. This clearly distinguishes it from sibling tools like build.build_release_candidate, which builds a release candidate, and ios.build_app, which builds iOS apps.

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 such as build.build_release_candidate or build.detect_project. It does not mention preconditions like needing a detected project or when choosing between debug and release builds. The use context is only implied by the tool name and the sibling set, not explicit.

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 structured annotations, the description carries the full burden of behavioral disclosure. It includes bracketed tags [approval required][workspace write][network][risk:dangerous] that clearly signal side effects, privilege, and danger. It also states that release signing is delegated to the target project, which is important context. It does not detail what gets overwritten or the final artifact location, but the risk profile is well communicated.

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 exceptionally concise: one sentence with risk/approval tags front-loaded, followed by a clear statement of the core function and a note about signing delegation. No filler words or redundant details. Every part earns its place.

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

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

For a tool with one optional enum parameter and no output schema, the description covers the high-risk side effects and signing delegation. However, it omits what the tool returns (e.g., APK path) and does not explain how 'kind' influences behavior. Given the tool's build context and the presence of sibling build tools, this is a moderate gap that prevents full autonomous 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 description coverage is 0% and the description does not mention the 'kind' parameter at all. Although the schema itself enumerates allowed values (flutter, react-native, android), the description provides no additional meaning about how kind affects the build or which value to select. Since coverage is low and the description fails to compensate, parameter semantics are minimal.

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 ('Build a release candidate APK') with a specific resource type. It distinguishes itself from sibling tools like build.build_debug_apk by naming 'release candidate' and mentions delegation of release signing. This gives an unambiguous 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?

No explicit guidance on when to use this tool versus alternatives such as build_debug_apk or flow.run_script. The tags imply approval and risk, but there is no statement of conditions or exclusions. The agent must infer usage from the name and generic build 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 the full burden of behavioral disclosure. The verb 'List' implies a non-destructive read, but the description doesn't disclose return shape, whether logs persist after listing, ordering, or any side effects. For a tool with zero annotation coverage, this is a meaningful 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?

A single efficient sentence with no wasted words; every element (verb, resource, scope qualifier) earns its place. It is front-loaded and scannable, though it could add a brief usage note without becoming verbose.

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 with no output schema, the description is mostly adequate: it states the resource and scope. However, it doesn't clarify what the returned log artifacts contain, when logs are available, or how this differs from the similarly named sibling collectors, leaving some ambiguity for an agent.

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

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

The tool has zero parameters and schema description coverage is 100%, so the baseline is 4. There are no parameter semantics to document, and the description's 'emitted by this MCP server' qualifier adds useful scoping meaning beyond the empty 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 states a specific verb ('List') and a specific resource ('build log artifacts emitted by this MCP server'). The qualifier 'emitted by this MCP server' helps distinguish it from sibling log-collection tools like device.pull_logs and ios.collect_logs, though it doesn't explicitly name 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?

No guidance is given on when to use this tool versus similar siblings such as ci.collect_artifact_manifest, device.pull_logs, or verify.collect_evidence. Usage context is only implied by the tool name and minimal description, with no exclusions or alternative routing.

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

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

No annotations are provided, so the description carries the full burden. It doesn't disclose how detection works (e.g., filesystem inspection, config file parsing), what the output format is, or whether it can fail/return unknown. The description is too thin to give an agent confidence about the tool's 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?

One short sentence that is front-loaded with the verb and lists the three project types. It is concise and scannable, though it could add a bit more context without becoming bloated.

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 minimal but the lack of output schema and behavioral detail leaves gaps. An agent doesn't know what the return value looks like (e.g., a string enum, a structured object) or how to handle an unrecognized project type. Given the tool's role in a build pipeline, this is a meaningful gap.

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. Baseline 4 for zero-param tools 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 a specific verb ('Detect') and resource ('Flutter, React Native, or native Android project type'), making the tool's purpose clear. It doesn't explicitly distinguish from siblings, but the sibling list contains no other detection tool, so the purpose is unambiguous enough.

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

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

The description implies the tool is used to determine project type before build/install steps, but it doesn't state when to use it versus alternatives or what to do with the result. No explicit exclusions or alternative routing 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?

With no annotations provided, the embedded flags approval required, workspace write, network, and risk dangerous carry the behavioral disclosure burden, and they clearly warn that this is a side-effecting operation that needs approval and network access. The description does not detail which files are modified, but the workspace-write and dangerous flags convey the essential risk profile. No contradiction with annotations exists because there are no annotations.

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 compact sentence with high-signal risk flags in front, followed by a clear purpose. There is no redundant explanation or filler; every part earns its place.

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

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

For a tool with one optional parameter and no output schema, the description covers purpose and safety but leaves workflow details unstated, such as what happens if no project is detected or how this integrates with build.detect_project. The core calling decision is mostly supported by the schema enum, but the operational context around detection and side effects is incomplete.

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

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

Schema description coverage is 0%, so the description must compensate for the undocumented kind parameter. The phrase specified mobile project type hints at how to influence the parameter and detected suggests behavior when it is omitted, but it never names kind or lists the enum values. The schema enum supplies the valid values, but the description adds only partial semantic context.

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 clear action and object: install dependencies for a mobile project type. It does not explicitly name sibling tools, but the dependency-installation purpose is distinct from ios.install_app and build.run_lint. The phrase detected or specified adds some scope without listing the supported project types.

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 this tool is used after a project type is detected or when the caller specifies one, which gives a weak usage condition. It does not name when to prefer this over sibling build tools or state exclusions, so the guidance is implied rather than explicit.

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. The prefix '[approval required][workspace write][network][risk:dangerous]' explicitly discloses side effects, permissions, and risk beyond the minimal action statement. It stops short of explaining failure behavior, but this is strong transparency for a simple run command.

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 clause with compact risk tags and no filler. It is front-loaded with behavioral warnings and states the action and scope immediately.

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 one-parameter tool with no output schema, the description covers the action, target platforms, and side-effect profile. It remains incomplete because it provides no usage heuristics, no guidance about omitted 'kind', and no indication of what the command returns or how lint failures are signaled.

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 only parameter, 'kind', has an enum but no schema description. The description's phrase 'for Flutter, React Native, or Android' mirrors the enum values and clarifies that kind maps to target framework, adding some meaning, but it does not explain default behavior when the optional parameter is omitted.

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 clear action ('Run lint/static analysis') with an explicit resource scope ('for Flutter, React Native, or Android'). This distinguishes it from siblings like build.run_unit_tests and build.build_debug_apk without ambiguity.

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 on when to prefer run_lint over sibling build tools, nor any when-not-to-use guidance. The platform list is useful scope information, but the agent is left to infer when linting is appropriate.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. It opens with '[approval required][workspace write][network][risk:dangerous]', which clearly signals side effects, permission requirements, and risk. It does not detail which workspace files may change, but the explicit danger and network flags provide substantial transparency beyond the schema.

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

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

The description is one compact sentence, with the risk and approval flags front-loaded. Every part contributes directly to safe invocation and understanding, with no 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 description covers purpose, supported platforms, and risk profile, which is a strong baseline for a simple one-parameter tool. However, it omits the default behavior when `kind` is not provided and gives no indication of command output or return value, which matters because there is no output schema to fill that gap.

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 has one parameter with 0% description coverage, so the description must compensate. It lists the supported frameworks, which mirrors the enum values in the schema, but it never names the `kind` parameter, explains that it is optional, or describes what happens when it is omitted (e.g., auto-detection). The description adds little semantic value beyond restating the enum.

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 action ('Run unit tests') and enumerates the supported project types ('Flutter, React Native, or Android'), which clearly distinguishes it from sibling build commands like build.run_lint and build.build_debug_apk. The scope is immediately understandable and not a tautology of the tool name.

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. The description implies it is for unit testing on the listed platforms, but it does not mention conditions, prerequisites, or exclusions such as 'use build.run_lint for static analysis' or 'run after install_dependencies.' The usage context is left to inference.

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 must carry the behavioral disclosure burden. It clearly states the core behavior and scope, but it does not disclose whether the manifest is returned to the caller, written to disk, or merely logged. The word 'Create' implies a side effect, yet no detail is given about mutation, output destination, or failure behavior.

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

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

The description is a single, focused sentence with no filler. It front-loads the action and immediately states the scope. Every word contributes to the meaning.

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 zero-parameter tool this is mostly complete, but there is no output schema and the description does not clarify where the manifest is produced. An agent knows the tool creates a JSON manifest of the artifacts directory, but not whether it gets the manifest in the response or must read it from somewhere afterward.

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 an empty schema, so there is nothing for the description to clarify. The baseline of 4 for a zero-parameter tool is appropriate because no parameter semantics are needed and the description does not introduce confusion.

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 ('Create'), names the concrete output ('a JSON manifest'), and scopes it precisely ('of files under the MCP artifacts directory'). It clearly states what the tool does and is distinguishable from all sibling tools by its unique output and directory scope.

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 indication of when to use this tool versus alternatives, such as after a build or before evidence collection. It does not mention any preconditions, intended CI stages, or what makes this tool preferable to other artifact-related tools like verify.collect_evidence or ci.write_github_step_summary.

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 well by declaring '[approval required][workspace write][network][risk:dangerous]'. It also discloses the underlying gh mechanism and the current-PR fallback behavior. It stops short of describing failure modes or side effects, but the explicit risk and permission tags are 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 compact and front-loads the most important risk and permission context before the action. Every clause earns its place, and the current-PR fallback is stated without unnecessary wording.

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 dangerous network/write tool with no annotations and no output schema, the description is too thin. It does not explain how body vs bodyPath should be supplied, what happens on failure, or what the agent should check before calling; the risk tags alone do not make the tool safe to invoke.

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%, so the description must compensate, but it only clarifies prNumber via 'Uses current PR when prNumber is omitted.' The body and bodyPath parameters are left entirely unexplained, including whether they are mutually exclusive or whether one is required.

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+resource: 'Create a GitHub PR comment through gh.' The tool name ci.comment_pr matches the described action, and the resource is distinct from siblings like code.open_pr and ci.create_github_annotations, so an agent can tell what this tool does.

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 phrase 'Uses current PR when prNumber is omitted' gives practical operational guidance for the common case. However, there is no explicit comparison to alternatives or conditions for when not to use this tool; the usage context is only implied by the action itself.

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 behavioral disclosure burden. The embedded '[workspace write][risk:write]' prefix openly signals that the tool performs a write and carries risk, which is meaningful transparency. It does not go into undo-ability or CI environment prerequisites, but for a simple annotation-emission tool the side-effect disclosure is solid.

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 the risk/context prefix front-loaded. There is no filler or redundancy; every token contributes.

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 3 parameters, 0% schema coverage, no output schema, and no annotations, the description is too thin. It omits parameter semantics, prerequisites like running inside a GitHub Actions environment, and the relationship between 'level', 'title', and 'findings'. An agent needs more context to invoke this reliably.

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%, so the description must compensate for the undocumented parameters. It only hints at the 'findings' array via 'from findings', and gives no meaning for 'level' or 'title'. With three parameters and one required, this is insufficient to let an agent construct a correct call without guessing.

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 verb ('Emit'), a specific resource ('GitHub Actions warning/error annotations'), and an input source ('findings'). This clearly differentiates it from sibling CI tools like ci.write_github_step_summary and ci.comment_pr, which target different GitHub surfaces.

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 in a GitHub Actions CI context where findings need to surface as annotations, but it gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or conditions that would select ci.write_github_step_summary or ci.comment_pr instead.

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 does include inline tags '[workspace write]' and '[risk:write]' and the verb 'Append', signaling it's a non-destructive write operation with workspace side effects. However, it omits details about the fallback file's path, environment detection, or error conditions, so transparency is only partial.

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, front-loaded with behavioral risk tags, followed by a clear action and target. There is no fluff, and every word contributes to the core meaning. It is concise without sacrificing essential scope.

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 write tool with two optional parameters, no annotations, and no output schema, this description is incomplete. It does not explain the purpose of sourcePath, when the fallback file is used, or how the agent should parameterize the call. The lack of parameter details and behavioral edge cases leaves too many gaps for safe 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 0%, so the description must compensate. It implies 'markdown' is the content to append, but 'sourcePath' is only vaguely tied to the workspace fallback file, with no explicit mapping or usage guidance. The description fails to explain either parameter clearly, leaving the agent to infer too much.

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 'Append' and names a concrete resource: 'GitHub Actions step summary or a workspace fallback file.' This clearly distinguishes it from sibling tools like ci.comment_pr and ci.create_github_annotations, which target different outputs. The purpose is immediately apparent.

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 offers no explicit guidance on when to use this tool versus alternatives. It does not mention CI environments, prerequisites, or when to prefer this over, say, ci.comment_pr. The fallback file is mentioned but not as a decision criterion.

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 it does so well: it discloses approval requirement, workspace-write mutation, dangerous risk, and the path-validation rule before touching any files. It falls just short of full transparency because it doesn't describe what happens on validation failure, partial application, or how to revert the change.

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 compact sentence with the safety badges front-loaded before the operative verb. Every phrase carries operational value and there is no repeated schema information.

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

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

For a simple one-parameter tool, the description covers the core operation, input type, and safety constraints. It is less complete because there is no output schema and the description does not indicate what the tool returns on success or error, nor does it specify the patch format beyond 'unified diff'; an agent may still have to discover those details.

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%, so the description must add meaning. It adds that the patch must be a unified diff and that touched paths are restricted, but it gives no formatting details, path-root conventions, or example of the expected patch syntax. For a single required string, this is adequate but leaves room for ambiguity.

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 operation (Apply a unified diff) and a distinct resource/scope (workspace files after path validation), which clearly separates it from sibling read/search/diff/commit tools. This is more than a tautology and lets an agent select it immediately.

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 verb 'Apply' plus 'unified diff' makes the use case inferable: use this when you have a patch to apply to code in the workspace. However, it never states when not to use it or names alternatives such as code.commit_changes for committing, so the guidance is implied rather than explicit.

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显得. The [approval required][workspace write][risk:dangerous] tags convey safety-critical traits, and the branch restriction adds important context. However, it does not disclose whether the commit is local-only or pushed, how all changes are staged when paths is omitted, or what the return value looks like.

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 compact sentences with no redundant wording. Safety markers are front-loaded, followed by the core action, a precondition, and the optional parameter, making it easy to scan and process.

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 essential purpose, the branch precondition, and the risk profile, which is adequate for a simple commit operation. However, it leaves important behavioral details implicit, such as what happens when paths is not provided, whether the commit pushes to a remote, and how 'allowed' branches are determined. These gaps matter for a workspace-write tool with no output 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 0%, so the description must compensate. It does explain the paths parameter as 'non-secret paths' to stage, adding meaning beyond the raw array type. However, it does not clarify path format or the default when paths is omitted, and the required message parameter receives no semantic explanation beyond its obvious purpose.

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 'Commit changes' and distinguishes it from sibling tools like code.apply_patch, code.create_branch, and code.open_pr. The branch constraint and optional staging clarify exactly what the tool does and its scope.

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 phrase 'only while on an allowed feature/ai branch' provides an explicit precondition and implies that the tool should not be used on main or other disallowed branches. It does not explicitly name alternative tools, but for a commit operation the usage context is sufficiently 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 structured annotations, the description carries the behavioral burden and does so via inline risk tags: approval required, workspace write, and risk dangerous. It also discloses a side effect beyond the schema: the branch is checked out, not merely created. It adds meaningful behavioral context, though it does not describe failure behavior if the pattern is not matched.

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?

All content is packed into one front-loaded sentence plus one constraint sentence; there is no filler. The inline tags immediately communicate approval and risk before the action. It could only improve by defining the pattern, not by adding length.

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

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

For a simple one-parameter mutation, the description covers the action, approval requirement, workspace write risk, danger level, and naming constraint. The main omissions are the concrete allowedBranchPattern value and the approval/error workflow. Since there is no output schema and no structured annotations, the description is close to complete but not fully self-sufficient.

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

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

There is one parameter, branchName, and the input schema provides only its type, so schema description coverage is 0%. The description partially compensates by tying branch creation to allowedBranchPattern, giving the parameter policy meaning. However, it never defines what allowedBranchPattern actually is or what name formats are valid, leaving a significant gap.

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 concrete action ('create and checkout') and a specific resource ('guarded feature branch'), and adds a hard constraint ('must match allowedBranchPattern'). It is distinct from sibling code tools like git_diff, apply_patch, and commit_changes, though it never explicitly names an alternative. The terms 'guarded' and 'allowedBranchPattern' are left unexplained, so clarity is strong but not maximal.

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?

It provides useful context by restricting creation to feature branches and warning that approval is required and the branch name must match allowedBranchPattern. However, it does not explicitly say when to prefer this tool over another or give a when-not-to-use case. Selection guidance is mostly implied rather than directly stated.

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, but it only says 'Return git diff.' It does not explain whether it includes unstaged changes, untracked files, or the exact semantics of the staged parameter, nor does it clarify side effects or output 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 a single front-loaded sentence with no wasted words. It is concise, though it sacrifices useful detail that could have been included without much length.

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

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

For a tool with no annotations, no output schema, and an undocumented parameter, the description is too thin. An agent cannot reliably determine what the staged flag does, whether the diff is limited to the working tree, or what the returned output looks like.

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 has one optional boolean parameter ('staged') with 0% schema description coverage, and the tool description does not mention it at all. The name 'staged' hints at semantics, but the description adds no meaning about what true or false produces.

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 clear verb ('Return') and resource ('git diff') with a specific scope ('workspaceRoot'). It is unambiguous about what the tool does, though it does not explicitly differentiate itself from sibling code 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?

There is no guidance about when to use this tool versus alternatives like code.apply_patch or code.commit_changes. The intended context is only implied by the tool name and description; no prerequisites, exclusions, or decision criteria 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?

With no annotations provided, the description carries the full burden and does disclose important behavioral traits: approval required, workspace write, and dangerous risk. This goes beyond the schema and helps the agent understand side effects, though it could say more about what changes on the remote.

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 critical risk and approval markers. The single sentence is efficient, though 'current allowed feature branch' is slightly jargon-heavy.

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 4-parameter tool with no annotations and no output schema, the description leaves substantial gaps: parameter meanings, branch push behavior, failure modes, and expected result are not addressed. The risk markers help but do not make the definition 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 0%, so the description must explain meaning for title, body, base, and draft. It mentions none of them. The agent gets no help understanding parameter semantics beyond bare property names.

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 and resource: 'Open a pull request with GitHub CLI from the current allowed feature branch.' This unambiguously separates it from siblings like code.create_branch, code.commit_changes, and ci.comment_pr. The scope ('current allowed feature branch') adds useful precision.

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 the tool by requiring 'approval' and being from the 'current allowed feature branch,' but it never explicitly states when not to use it or names alternatives. Context is present, but exclusionary guidance is absent.

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 full behavioral burden. It discloses that only non-secret files within workspaceRoot are readable, implying read-only behavior and a scope restriction. However, it does not disclose return format, error handling (e.g., missing files, exceeding maxBytes), or permission requirements, leaving gaps 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 a single, compact sentence with no filler. It front-loads the core action and scope, and every word adds value. This is appropriately concise for a simple read 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 no output schema, no annotations, and 0% schema coverage, the description must provide complete context for the agent. It omits key details such as how maxBytes behaves, what happens for missing or oversized files, and the return value format. While the tool is simple, the description leaves several operational unknowns.

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%, so the description must compensate. It gives minimal context for 'path' (inside workspaceRoot) but says nothing about 'maxBytes' or its meaning. The description adds very little value beyond the schema's type and required fields, failing to explain key parameter behavior.

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 'Read' and the resource 'non-secret file inside workspaceRoot', clearly distinguishing this from sibling tools like code.search_code (search) and code.apply_patch (modify). The qualifier 'non-secret' adds an important scope boundary, making the purpose unambiguous.

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

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

The description implies usage when you need to read a file, but it does not explicitly state when to use this tool versus alternatives (e.g., search_code for searching, apply_patch for modifications). The 'non-secret' qualifier provides a minor exclusion (don't use for secret files), but no clear context or naming of alternatives is given.

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

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

The description discloses a meaningful behavioral trait: it uses ripgrep when available and falls back to a built-in scanner. This is useful context beyond the schema. However, with no annotations provided, the description carries the full burden and doesn't disclose other behaviors like case sensitivity, regex support, or whether results are limited by maxResults.

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 primary action and scope. It earns its place by adding the ripgrep fallback detail, though it could be slightly more informative about parameters.

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 search tool with 3 parameters, no output schema, and no annotations, the description is too sparse. It doesn't explain what the search returns, how glob filtering works, what maxResults does, or any limitations. An agent would need to guess at the behavior of the built-in scanner and the meaning of the parameters.

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

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

Schema description coverage is 0%, so the description must compensate for the undocumented parameters. It only mentions 'query' implicitly through 'Search workspaceRoot' and doesn't explain 'glob' or 'maxResults' semantics. The description adds minimal value beyond the schema's bare parameter names.

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 ('Search') and resource ('workspaceRoot'), which clearly identifies the tool as a code search function. It doesn't explicitly differentiate from siblings like code.read_file, but the search intent is clear enough to distinguish it from read/apply/commit operations.

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 context by mentioning the search scope (workspaceRoot) and the fallback mechanism, but it doesn't explicitly state when to use this tool versus alternatives like code.read_file or security.scan_source. No exclusions or alternative routing 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 of behavioral disclosure. It reveals the outcome (a PNG artifact) but does not explain device selection behavior, behavior with multiple connected devices, error conditions, whether it requires an Appium session, or how artifact naming works.

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 wasted words. It is appropriately brief for a straightforward capture tool, though it sacrifices explanatory detail that other dimensions needed.

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

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

With no annotations, no output schema, and 0% parameter description coverage, the tool leaves important context unstated: optional parameters, device selection defaults, and operational requirements. It is callable with zero arguments, but an agent choosing between Android and iOS capture tools gets no explicit routing or follow-up context.

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%, and the description does not explain the meaning of the optional 'prefix' or 'serial' parameters. An agent is left to guess what 'prefix' affects and how 'serial' selects a device, so the description adds no semantic value beyond the raw 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 states a specific verb and resource: it captures a PNG screenshot from an Android device into artifacts. It clearly distinguishes itself from ios.capture_screenshot and other device/appium tools by naming the Android platform and the output destination.

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 on when to use this tool versus ios.capture_screenshot or other screenshot-related tools, nor any mention of prerequisites like an active ADB connection or booted emulator. The platform mention implies Android-only usage, but no alternatives or exclusion conditions 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?

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose that this is a device mutation requiring approval and that it is dangerous, which is valuable. However, it does not explain that the operation is destructive and irreversible, what specific data is removed, or what happens to the app after clearing.

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 risk and mutation tags before the action. It contains no wasted words. However, its brevity comes at the cost of important usage and consequence details, so it is concise but not fully informative.

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?

This is a destructive device tool with no annotations and no output schema, so the description needs to explain the safety profile and invocation context thoroughly. The tags 'approval required', 'device mutation', and 'risk:dangerous' help, but the description does not state preconditions, irreversibility, or parameter semantics, leaving an agent under-informed for a high-risk action.

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%, so the description must compensate for the parameters. It only loosely maps to packageName by saying 'for an Android package' and gives no meaning for the optional serial parameter or expectations around package naming/format. This is minimal compensation for an otherwise undocumented 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 a specific verb and resource: 'Clear app data for an Android package.' This distinguishes it from nearby siblings like device.uninstall_app and device.install_app, since clearing app data is a distinct reset operation rather than removing or installing the app.

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 about when to choose this tool over alternatives, when not to use it, or what preconditions must hold, such as the package being installed or the device being online. The risk tags indicate approval and mutation, but they do not explain usage context or alternatives.

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?

Annotations are entirely absent, so the description must carry the burden. The brackets '[approval required][device mutation][risk:dangerous]' add critical behavioral context: the operation mutates the device and is dangerous, requiring explicit approval. This is valuable beyond what the schema provides. However, it does not disclose what happens on failure (e.g., if permission already granted, invalid permission name, permission not requestable), nor whether the grant is permanent or session-limited, nor if re-granting is idempotent. This is a partial disclosure.

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 risk markers before the action. It is efficient with no filler. The only minor flaw is that the risk markers could be seen as redundant with the action itself, but they still add value. The description earns its place.

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

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

The tool has no output schema, no annotations, and zero schema description coverage, so the description must fully specify behavior. It falls short: it does not explain what the success/failure response looks like (e.g., whether a JSON with granted permissions is returned), whether the operation is idempotent, on which Android versions this works, what permission format is expected (full string vs shorthand), or how 'serial' is used. For a dangerous device mutation with no annotations, this is a significant gap that could lead an agent to call it incorrectly.

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%, meaning the description must compensate for undocumented parameters. The description states 'one or more Android runtime permissions' which clarifies that 'permissions' is an array of runtime permission strings (e.g., android.permission.CAMERA), and 'packageName' is the target package. However, it does not explain 'serial' at all – whether it optionally targets a specific device or is required for multi-device setups. As a result, description partially compensates but leaves a gap.

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 (grant), the resource (Android runtime permissions to a package), and the required target package. It is distinct from sibling device mutation tools like install/uninstall/clear_app_data, so purpose is clear. The description does not name alternatives but the verb+resource is specific.

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 includes brackets indicating approval is required and that it is a device mutation with dangerous risk, which implicitly tells the agent to use caution and presumably ask for approval. However, it does not say when to use this tool versus alternatives or when NOT to use it (e.g., when a permission is already granted, or for non-runtime permissions). Context is implied but not explicit.

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 burden of behavioral disclosure. It openly marks the operation as 'device mutation' and 'risk:dangerous' and says it may 'replace' an APK, implying overwriting behavior. This is valuable safety-relevant information beyond the schema. It does not detail data-loss nuances or interaction with an existing installation, but it covers the essential risk profile.

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 compact sentence with useful risk tags front-loaded, and every phrase contributes meaning. It is not bloated. It loses a point only because the brevity contributes to missing parameter and usage details, though those are penalized elsewhere; structurally it is efficient.

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

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

With no annotations and no output schema, the tool description should provide enough context to call the tool correctly. It does not explain the meaning or optionality of serial, the expected format or location of apkPath, prerequisites, or what happens upon successful installation. For a mutation tool labeled 'dangerous', this is insufficiently 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 0%, so the description must define the parameters, but it only mentions 'APK' generically and never explains 'apkPath' or 'serial'. It is unclear whether apkPath is host-local or on-device, whether serial is optional or required, or how the tool selects a device when serial is omitted. The description adds almost no semantic value beyond the parameter names.

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 clear verb-resource pair: 'Install or replace an APK on an Android device.' It explicitly targets Android, which separates it from sibling ios.install_app, and 'replace' distinguishes it from device.uninstall_app and other device-related tools. This is specific enough for an agent to understand exactly what the tool does.

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 only implied: the mention of 'Android device' and the sibling ios.install_app suggest when this tool should be used versus the iOS equivalent. However, the description does not state exclusions, prerequisites (e.g., APK path source, device connectivity, whether serial is required), or when to prefer a sibling like device.uninstall_app first. It is minimally adequate but lacks explicit 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?

There are no annotations, so the description carries the full burden of disclosing behavior. 'List' and the `adb devices -l` reference make it clear this is a read-only enumeration, but the description does not mention output format, failure states, or that it only shows currently connected devices.

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 direct sentence that says exactly what the tool does and how. There is no redundant wording 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?

For a zero-parameter listing tool, the description is nearly complete. It identifies the target platform and the exact command, though it stops short of describing the expected output shape or edge cases like unauthorized or offline devices.

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, so there is nothing for the description to clarify. The schema already fully documents the empty parameter set, and the description does not need to compensate.

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 ('List') and the resource ('Android devices'), and names the underlying command (`adb devices -l`). This makes it immediately distinguishable from sibling tools like ios.list_simulators or device.start_emulator.

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

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

The description implies the tool is for enumerating connected Android devices, but it does not explicitly state when to prefer it over alternatives or mention any prerequisites. The use case is fairly obvious from the name, but there is no explicit when/when-not 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 of behavioral disclosure. It does not mention side effects (e.g., whether clearAfter clears the log buffer), prerequisites such as a connected device or adb access, or what 'into artifacts' means for the caller. The vague 'when available' clause adds little concrete 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 short, front-loaded with the main action, and has no filler. The second sentence is somewhat awkward ('package pid', 'when available') and could be clearer, but it does not bloat the definition.

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 four undocumented optional parameters, no annotations, and no output schema, two sentences are insufficient. The agent is left to guess which optional parameters matter, whether a serial is needed, what the artifact output looks like, and what constraints apply to logcat collection.

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%, and the description only vaguely touches one parameter via 'filter by package pid when available'. serial, clearAfter, and outputPath are left entirely unexplained, so an agent cannot determine their meaning, defaults, or how they interact.

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 verb ('Pull'), a specific resource ('Android logcat'), and a concrete outcome ('into artifacts'), which separates it from iOS- or build-log tools such as ios.collect_logs or build.collect_build_logs. The optional filter sentence adds scope without obscuring the primary action.

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 phrase 'Android logcat' implies the tool is for Android device logs, which gives some selection context relative to iOS/build log siblings. However, there is no explicit when-to-use guidance, no mention of alternatives, and no exclusions or prerequisites, so the agent must infer usage from the tool name and domain.

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?

Despite no annotations being provided, the description front-loads important behavioral flags: 'approval required,' 'device mutation,' and 'risk:dangerous.' It also discloses completion behavior ('Returns after launching or optional boot wait'), which is meaningful for a mutation tool. However, it does not describe failure modes, side effects, or state changes beyond starting an emulator.

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 efficient. The risk flags appear first, followed by a clear one-sentence specification of the action and return behavior. No filler words are present.

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 annotations, no output schema, and three parameters, the description is thin. It fails to explain timeoutMs, mention how to obtain valid AVD names, describe what happens if the emulator is already running, or provide any error/failure semantics. The description does not fully equip an agent 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 0%, so the description must compensate. It explains avdName ('by AVD name') and partially covers waitForBoot ('optional boot wait'), but timeoutMs is never described. The meaning, units, and behavior of timeoutMs are left entirely unspecified, leaving a significant gap.

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: 'Start an Android emulator by AVD name.' This clearly identifies the tool's function and distinguishes it from siblings like device.stop_emulator and ios.boot_simulator. The scope is unambiguous.

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

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

The description implies usage through its name and wording, but there is no explicit guidance on when to use it versus alternatives, no preconditions such as listing available AVDs first, and no exclusion such as 'for iOS, use ios.boot_simulator.' Usage context is left to inference.

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

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

No annotations are provided, so the description carries the full burden. It includes tags 'approval required', 'device mutation', and 'risk:dangerous' which disclose that this is a destructive, risky operation requiring approval. This provides useful behavioral context, though it does not elaborate on side effects or reversibility. Given the absence of annotations, this is a reasonable disclosure.

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

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

The description is extremely concise: a single sentence with front-loaded warnings followed by the core action. Every part is informative, and there is no wasted text. It efficiently communicates the tool's purpose and risk.

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 simplicity, the description is still incomplete: it fails to explain the 'serial' parameter, and does not describe any preconditions, output, or post-conditions. The warnings cover safety, but the parameter gap and lack of usage context leave the agent without enough information to invoke the tool reliably.

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

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

The input schema has one parameter 'serial' with no description, and schema description coverage is 0%. The tool description does not mention 'serial' at all, leaving its meaning, format, and how to obtain it entirely unexplained. The agent has no guidance on what to provide for this parameter.

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 ('Stop'), a clear resource ('Android emulator'), and the method ('adb emu kill'). This clearly distinguishes it from siblings like device.start_emulator or device.list_devices, so an agent can identify its purpose without ambiguity.

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

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

The description does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. However, the purpose is self-evident from the action, and the presence of sibling tools like device.start_emulator makes the usage context clear by contrast, but no explicit guidance is given.

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

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

No annotations are provided, so the description carries the full burden. It includes tags for 'approval required', 'device mutation', and 'risk:dangerous', which disclose that this is a destructive, permission-sensitive operation. However, it does not explain what happens to app data, whether it affects other users, or any recovery options. The disclosure is minimal but present.

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 line with safety tags front-loaded. Every word adds value and there is no fluff.

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

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

Given the simplicity of the operation, the description is adequate but not complete. It lacks details on the return value (e.g., success/failure), any prerequisites (like device being online), and the effect of the optional serial parameter. With no output schema and no parameter explanations, an agent may still need to infer details. The risk tag covers some context but not all.

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%, and the description does not mention either parameter (serial or packageName). The description adds no meaning beyond what the schema already shows, and it fails to compensate for the low coverage. The parameter names are self-explanatory, but the description should at least note that packageName is required or how serial affects the target device.

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 (uninstall) and the resource (an Android package from a device), which distinguishes it from siblings like install_app or clear_app_data. The verb and object are specific and unambiguous.

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

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

The description gives no explicit when-to-use or when-not-to-use guidance. While the purpose makes it obvious this is for removing an app, it does not mention alternatives (e.g., clear_app_data for resetting) or conditions like device requirements. The context is implied rather than stated.

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 burden of behavioral disclosure. 'Return' implies a read-only operationcase, but the description does not explicitly state that it is side-effect-free, whether it requires network access, or whether it queries local metadata.

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, precisely worded sentence conveys the entire purpose with no filler. The key noun phrase 'supported host/platform requirements' is front-loaded and unambiguous enough for agent selection.

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, low-complexity query, the description is minimally adequate. However, it provides no hint of the return format, whether the result is a list or a structured object, or how this might feed into preflight checks, so an agent must call the tool to learn more.

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 description coverage is 100%, so the schema is complete. The description adds relevant meaning about what the returned information represents, keeping this at the baseline 4 for parameterless tools.

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 ('Return') and the resource ('supported host/platform requirements for this MCP package'). It is distinguishable from sibling environment tools like env.preflight and env.ensure_appium, though it does not explicitly name 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?

There is no guidance on when to use this tool versus alternatives such as env.preflight or build.detect_project. The description only says what it returns, not under what circumstances an agent should call it.

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

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

With no annotations supplied, the description carries the behavioral burden. It discloses that the tool can write to the workspace, use the network, require approval, and that a server it starts is detached. It does not detail idempotency or handling of an already-running server, but the included risk tags and 'detached' are substantive.

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 filler. The risk tags lead and the core action plus optional behaviors follow immediately.

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 optional parameters, no output schema, and no annotations; the description gives only an overview. An agent still lacks guidance about expected return value/readiness signal, meaningful defaults beyond detached server start, and which parameter combinations are common or required for a successful setup.

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% and the description names none of the 10 parameters. It only alludes to driver installation and server startup at a high level, leaving port, address, appiumHome, timeoutMs, useNpx, and others unexplained. Description does not compensate for the schema gap.

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 ('Check Appium readiness') with explicit optional behaviors ('install a driver', 'start a detached Appium server'). This clearly distinguishes it from sibling tools like appium.create_session or env.preflight, which cover different lifecycle stages.

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 wording implies this is a setup/preflight tool to run before Appium sessions, and the optional install/start flags hint at the intended use. However, there is no explicit guidance on when to choose this over env.preflight or appium.create_session, and no alternatives are named.

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 the full behavioral burden. It only says 'check', implying a read-only operation, but does not disclose whether it modifies anything, what it returns, or any side effects. It also omits operational details like network access or installed tooling requirements. This is a significant gap for a tool that likely performs environment inspection.

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 verb and object. It wastes no words and is easily parsed. However, it is so brief that it omits crucial detail, which is a structure vs. completeness trade-off, but for conciseness alone it earns a 4.

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 simplicity (one optional parameter, no output schema, no annotations), the description still lacks essential information: what 'readiness' actually checks (e.g., SDK versions, environment variables), the format of the result, and the acceptable values for 'target'. An agent would struggle to use this tool correctly without additional context.

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 has one optional parameter 'target' with zero description (0% coverage). The description hints that 'target' selects an environment (Android, iOS, etc.) but does not specify valid values, the default behavior when omitted, or whether it accepts comma-separated lists. The agent cannot reliably construct the correct input without guessing.

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: checking host/project readiness across specific environments (Android, iOS, Flutter, React Native, CI) or all. This is a specific verb-resource pair and distinguishes it from siblings like env.ensure_appium (which ensures Appium) and env.compatibility_matrix (which builds a matrix).

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

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

The description implies the tool is used to assess readiness before proceeding, but it does not explicitly state when to use it instead of alternatives, nor does it mention any exclusions or prerequisites. The environment list gives context, but there is no direct guidance on selection criteria compared to related 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. It implies a read-only analysis operation ('infer...from source code') but does not state whether it modifies files, what inputs it requires beyond the optional parameters, what side effects it might have (e.g., heavy computation), or how results are returned. This is a minimal hint of behavior, not enough for safe invocation.

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 that states the core purpose without unnecessary words. It earns its place by conveying the operation and expected outputs efficiently. However, it is so brief that it omits essential contextual and parameter information, slightly reducing structural quality.

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 (2 optional parameters, no output schema, no annotations), the description is insufficiently complete. It does not explain what the tool returns, how the source code is identified, what the parameters do, or any conditions for successful execution. An agent would be guessing about critical invocation details.

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%, and the description does not mention maxFiles or includeTests at all. The agent cannot determine the meaning, effect, or appropriate values of these parameters from the description. Since the schema only provides names and types, the description must compensate but fails to do so.

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 ('infer') with a concrete resource ('mobile screens, routes, transitions, and visible text candidates') and a clear source ('source code'). This clearly distinguishes it from sibling tools like code.search_code or code.read_file, which do not infer UI structure, and from flow.generate_test_scenarios, which generates scenarios rather than analyzing code.

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 on when to use this tool versus alternatives. The description does not mention prerequisites, such as needing a mobile project context, nor does it contrast with similar analysis tools. An agent has to infer the intended use case solely from the tool name and one-line description.

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 includes useful inline tags: [approval required], [workspace write], and [risk:dangerous]. It also explicitly discloses that source code is untouched. It stops short of describing irreversibility or what specifically is deleted from flow memory, but the core side effects are surfaced.

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 plus compact risk tags. It front-loads the action and safety classification and every sentence adds information 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?

For a dangerous, approval-required destructive tool with no output schema, the description is incomplete. It omits when this tool should be used, what clearing memory entails for active flows/checkpoints, and how the confirm parameter should be satisfied. The risk tag and artifactsDir scope are useful but do not make the definition callable without further inference.

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% and the description never explains the required confirm parameter. An agent cannot tell from the description what value confirm should hold, how it relates to the approval requirement, or any required confirmation string. The tool description adds no parameter-level meaning beyond the bare name 'confirm'.

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 and resource: 'Clear flow memory under artifactsDir.' It clearly states what is affected and adds an important scoping statement that app source code is not modified. However, it does not explicitly differentiate from flow.read_memory or related flow lifecycle tools beyond the verb itself.

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 on when to call clear_memory versus alternatives like flow.read_memory or flow.record_checkpoint. The 'does not modify app source code' note is a safety clarification, not a usage condition, so an agent is left to infer when this destructive reset 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 of behavioral disclosure. It says 'generate' and 'from static source-flow analysis,' which hints at a read-only analysis, but it does not state whether the tool has side effects, requires prior code analysis, returns a formatted list, or interacts with external systems. This is a significant gap for a tool that produces candidate scenarios.

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, tight sentence with no redundant words. The core action is front-loaded ('Generate candidate mobile E2E scenarios') and the rest adds necessary context about the source and consumer. Every word earns its place.

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

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

The tool has five optional parameters, no output schema, and no annotations, yet the description provides no information about parameter semantics, return format, prerequisites, or how the generated scenarios are delivered. For a tool an agent must invoke correctly, this is severely under-specified and leaves critical operational details to guesswork.

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% — none of the five parameters (goal, maxFiles, includeTests, maxScenarios, includeNegativeCases) have descriptions in the schema. The tool description does not mention any of these parameters or their meaning, so an agent cannot determine what values to pass. With zero coverage, the description must compensate, but it does not.

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 ('Generate'), a specific resource ('candidate mobile E2E scenarios'), and a distinctive source ('static source-flow analysis'). It clearly differentiates from siblings like flow.analyze_from_code and security.generate_test_plan by naming exactly what is produced and for whom. The phrase 'for an AI agent to execute/refine' further clarifies the output's role.

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

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

No explicit guidance is given on when to use this tool versus alternatives. It does not reference any sibling tool or exclusion criteria (e.g., 'use this when you have completed flow analysis' or 'for security-focused plans, use security.generate_test_plan'). The phrase 'from static source-flow analysis' implies a precondition but provides no decision rule for choosing this tool.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only planning behavior by saying it 'returns' actions but does not disclose whether any state is mutated, whether prior recorded checkpoints must exist, what happens on no match, or how matching works. Key behavioral gaps remain for a tool with no annotation coverage.

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, front-loaded with the main action and expected output. There is no filler or redundancy, and it is easy for an agent 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 high complexity (7 parameters, 0% schema coverage, no output schema, no annotations), the description is too sparse. An agent cannot determine what inputs are required, what the returned Appium actions look like, or how this tool relates to flow.replay_to_checkpoint. It serves as a high-level summary but not a usable invocation guide.

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%, and the description does not explain any of the 7 parameters. 'target checkpoint' loosely maps to targetCheckpointId, but source, sourcePath, serverUrl, sessionId, testName, and minimumScore remain entirely undocumented. The description does not compensate for the absent schema documentation.

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: compare the current screen to recorded checkpoints and return Appium actions needed for a target checkpoint. It is specific about the verb and resource, but it does not explicitly differentiate from the sibling flow.replay_to_checkpoint, so it falls short of a 5.

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 on when to use this tool versus alternatives like flow.replay_to_checkpoint or flow.record_checkpoint. There are no exclusions, preconditions, or selection criteria. The intended usage is only implied by the wording, not stated.

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

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

No annotations are provided, so the description carries the full burden. It communicates a read operation, but it does not disclose what the tool returns, whether it reads all recorded memory or only the latest state, whether it has side effects, or any ordering/filtering 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?

A single sentence with no filler. The core action and resource are front-loaded, and every word contributes to the tool's meaning.

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 read tool, the description is minimally viable, but it lacks return-format details and any guidance on how to interpret or consume the read results. The low complexity keeps this from being lower, but the missing behavioral context prevents a higher score.

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 is empty and parameter coverage is effectively 100%, so there are no parameter semantics for the description to clarify. The zero-parameter design makes this dimension straightforward.

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 ('Read') and identifies a clear resource ('recorded flow checkpoints, runs, and code-flow analyses'). This distinguishes it from the flow.record_* and flow.replay_* siblings, though it does not explicitly name an alternative.

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 such as flow.plan_replay, flow.replay_to_checkpoint, or loop.read_iterations. It implies a retrieval use case but does not state exclusions or prefer conditions.

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