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 discloses that the operation is a read-style listing, that matching is case-insensitive, and that output is one line per chat with specific fields (ROWID, name, last message time, message count). It does not mention ordering or pagination, but the core behavior is transparent.

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

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

The description is two tightly written sentences. It front-loads the core purpose, then adds filtering behavior and return format without any filler or redundant schema restatement.

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 only two optional parameters and an output schema, the description covers the important behavioral choices: listing, optional filtering, case-insensitivity, and returned fields. It is slightly incomplete only in not elaborating on what 'recent' means or how 'limit' affects the result, but these are minor given the schema defaults and 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 schema itself contains no parameter descriptions (0% coverage), so the description must compensate. It does well for 'query' by explaining case-insensitive substring matching against chat name, contact names, or chat identifier, but it provides no semantics for 'limit' beyond what the parameter name and default already imply.

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

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

The description uses a specific verb ('List') with a clear resource ('recent iMessage/SMS chats') and details optional filtering by substring against chat name, contact names, or identifier. It also specifies the output shape, making the tool's purpose immediately 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 clearly implies when to use the tool: when you need a recent chat list, optionally narrowed by a text query. It does not explicitly contrast with sibling tools like search or read_thread, but the listing behavior is stated well enough that an agent would rarely confuse it with those 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, the description carries the behavioral burden and does so well: it discloses chat identifier/name/substring forms, ambiguous-name candidate-list behavior, the date-time format for since, and the limit/ordering nuance. It omits edge cases like no-match handling, but still conveys substantial non-obvious 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 compact and well-structured: purpose first, then each parameter's semantics in turn. Every sentence adds distinct value without repeating schema defaults or titles.

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 three-parameter read-only tool with an output schema available, the description covers the main callability concerns: chat resolution, time filtering, and limits/ordering. Minor gaps such as no-match behavior or the default of since do not prevent 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 description coverage is 0%, and the description fully compensates by explaining exactly what chat accepts, what since means and its accepted formats, and how limit affects result selection and ordering. This is the semantic information an agent needs beyond the raw 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?

States a specific action ('Read messages from one chat') with a clear resource, scope, and ordering guarantee. The one-chat focus clearly separates it from sibling tools like list_chats, search, and send.

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

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

The description provides clear context for when to use this tool: reading a single chat's messages in date order. It doesn't explicitly name alternatives or exclusion conditions, so it stops short of full routing 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?

No annotations are provided, so the description carries the behavioral burden. It discloses meaningful behavior: search targets decoded bodies, matching is case-insensitive, and the since parameter accepts specific date/time formats. It does not explicitly state read-only status or pagination behavior, but 'search' implies non-mutating and the output schema covers return shape.

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

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

The description is compact and front-loaded with the core action. The second sentence adds only useful optional-filter details, with no filler or repetition of 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 4-parameter tool with an output schema, the description covers the required text parameter and the non-trivial optional filters, including accepted date formats. The one unmentioned parameter, limit, is adequately defined in the schema with its name and default, so an agent has enough information 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 adds real semantics for text (case-insensitive substring), chat (optional restriction with matching rules aligned to read_thread), and since (on-or-after with two accepted formats). The limit parameter is not mentioned, but its schema title and default value of 50 make it self-explanatory.

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

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

The description opens with a specific verb and resource: 'Search decoded message bodies for a substring (case insensitive).' It also references read_thread for chat matching rules, which helps differentiate this tool from sibling tools like list_chats and read_thread.

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 main use case—locating messages by substring—and explains optional chat and since filters. However, it does not explicitly state when to prefer search over read_thread or list_chats, nor does it provide exclusions. The 'same matching rules as read_thread' note is about parameter behavior, not tool selection.

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

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

With no annotations provided, the description carries the full behavioral burden. It discloses that sending is disabled by default, requires an environment variable, follows chat matching rules like read_thread, and mandates explicit user confirmation. This gives an agent meaningful safety and prerequisite context beyond the basic action.

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 core purpose is front-loaded, followed by critical activation and safety instructions. No wasted words or redundant restatement of the schema.

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

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

For a simple two-parameter tool with an output schema, this description covers the essential operational context: activation, chat resolution, and the mandatory consent gate. Nothing critical is missing for an agent to call 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?

Schema description coverage is 0%, so the description must compensate for both parameters. It adds useful semantics for `chat` by referencing read_thread matching rules, but it does not explicitly define `text` beyond the obvious 'message text' implied by the tool's purpose and the consent warning.

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

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

The description opens with a specific verb and resource: 'Send a message through Messages.app.' This clearly distinguishes sending from the sibling tools (list_chats, read_thread, search, whats_new) 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?

It provides explicit usage conditions: the tool is disabled by default, must be enabled via IMESSAGE_SEND=1, and must only be called after showing the exact text and getting user consent. It does not explicitly contrast with sibling tools, but the purpose is so distinct that exclusion feels implicit.

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 and does so well. It discloses the persistent cursor file location, the default mark_seen side effect that advances the cursor, and the grouping/ordering semantics. This gives an agent a realistic model of stateful 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 main purpose is front-loaded in a single precise sentence, followed by compact cursor mechanics. There is no filler, repetition of schema fields, or unnecessary detail.

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

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

For a stateful tool, the description covers the full lifecycle: first call, cursor location, default advancement behavior, grouping, and ordering. Since an output schema exists, omitting return-value details is acceptable.

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 only provides the parameter name, type, and default; the description explains that mark_seen controls whether the cursor advances and how that affects future calls. The false branch is not explicitly spelled out, but it is easily inferred from the described 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 first sentence states a precise operation: return every message across all chats since the cursor, grouped by chat with oldest first. This clearly distinguishes it from siblings like read_thread (single chat) and search, while the cursor mechanism separates it from list_chats.

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 clear context about first-call behavior and cursor advancement, but it never explicitly says when to prefer whats_new over read_thread, search, or list_chats. The polling use case is implied rather than stated with alternatives or exclusions.

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