What Matters

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

With no annotations provided, the description carries the full burden of disclosing side-effects. It reveals that adding with initiated:'auto' and priority:'high' immediately notifies the user's phone, explains that the interruption is the point, and warns against overuse. It also states the item bypasses review. This is excellent behavioral 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 four sentences and front-loaded with the core purpose. Every sentence adds value—usage rule, exception, and the warning about notification fatigue. It's dense but not bloated; only slightly verbose for the amount of content.

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

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

Given 10 parameters, no annotations, and no output schema, the description covers the key contexts: when to use, the two initiation modes, and the notification side-effect. It doesn't explain return behavior after adding, but that's largely implicit for an 'add' operation. Slightly more could be said about post-add confirmation, but the tool is well-specified overall.

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 90% description coverage and already explains initiated, priority, and other parameters. The description adds usage context for initiated (human vs. auto) and the high-priority exception, but it largely reinforces schema semantics rather than introducing new parameter meaning. Baseline of 3 is appropriate given high schema coverage.

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

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

The description opens with a specific verb and resource: 'Add an item immediately, without review.' It clearly scopes the tool to immediate, unreviewed additions and explicitly contrasts it with put_proposal, distinguishing it from sibling tools.

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

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

The description gives explicit when-to-use guidance: 'use this ONLY when the user has just asked for it in conversation' and explicitly redirects to put_proposal for scheduled scanning, with a clearly defined exception for genuinely urgent items. This is textbook usage differentiation.

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 transparency burden. It discloses idempotency and the reversible nature (reopen), which are key behavioral traits. It does not mention error behavior or return values, but the core behavior is clear.

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

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

Two short sentences, front-loaded with the action and idempotency. No wasted words, and the structure is easy to parse.

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 2-parameter tool with no output schema, the description is reasonably complete: it states purpose and idempotency. It lacks explicit error/response details, but these are not critical for such a straightforward toggle.

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 50%: the `done` parameter has a description, but `item_id` does not. The description adds meaning to `done` by tying it to 'done or reopen', but does not clarify `item_id` beyond the schema's format.

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

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

The description 'Mark an item done, or reopen it' uses a specific verb and resource, clearly distinguishing it from siblings like add_item and put_proposal. It directly states the action and the possible reverse 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?

Usage is implied: use when you want to change the done state of an item. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternatives are mentioned.

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

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

With no annotations, the description explains the importance of calling this read tool to avoid failure modes. However, it doesn't explicitly mention side effects or auth, but the read-only nature is clear from 'Read everything' and the guidance to call before changes.

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

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

Two sentences that are direct and front-loaded, with no redundant 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?

The description mentions the return contents (action items, dismissed, focus) and the workflow context, making it complete for a read tool without an 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 covers both parameters with detailed descriptions about include_rules and include_dismissed defaults and implications. The tool description does not add parameter-specific details, so baseline 3 applies.

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

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

The description clearly states the tool reads action items, dismissed records, and focus terms. It uses the verb 'Read' and specifies the resource, distinguishing it from mutation siblings like add_item and put_proposal.

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

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

Explicitly instructs to call before proposing changes, explains why (to avoid re-suggesting dismissed items), and identifies it as the only way to know what was deleted or rejected.

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

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

With no annotations provided, the description carries full behavioral burden and does it thoroughly. It discloses destructive semantics (omitting a term deletes it), trimming behavior for over-limit inputs, the return of the stored result, and the critical constraint that inferred terms must never be added. This goes well beyond what the raw schema or annotations would convey.

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

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

The description is dense but every sentence earns its place. It front-loads the primary purpose and replacement rule, then systematically covers read-before-write, limits, return value, and usage exclusions. Despite its length, there is no filler or redundant restatement of the tool name.

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 no annotations and no output schema, the description fully compensates by covering side effects, edge cases (trimming), return behavior, and policy constraints. It is complete enough for an agent to invoke correctly without needing 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?

Although the schema already describes the terms array as 'The complete list, in the order the user wants to see it', the description adds crucial constraints: send the WHOLE list, up to 10 terms of 60 characters, trimming rather than refusing, and the empty-array-clears behavior. These details are not in the schema and materially affect how to set the 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 opens with a specific action: 'Replace the list of things the user says matter most', clearly identifying the resource (the focus list) and the operation (replace). It also distinguishes itself from siblings by emphasizing replacement rather than appending, and by stating 'this replaces, it does not append'.

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?

Explicit guidance is provided: 'Read the current list from get_document first' names the companion tool to use before this one, and 'ONLY call this when the user asks you directly, in conversation. A scheduled run must never touch it' gives a clear when-to-use and when-not-to-use rule. This strongly differentiates from potential alternative uses.

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 discloses a critical behavioral trait: rules 'tak[e] effect IMMEDIATELY with no review'. While it doesn't detail reversibility or permissions, the most safety-relevant behavior is clearly 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?

Two sentences, front-loaded with the action and then the usage constraint. Every word earns its place; no 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?

Given the complex schema and no output schema, the description covers the essential selection context and key caveat. The schema handles parameter details and required fields. It could explicitly mention that 'create' requires the rule object, but the schema already implies this.

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

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

Schema description coverage is high (75%), with rich descriptions for channel, section, and reason. The description adds no parameter-level detail, but the schema already documents the parameters adequately, so the baseline 3 is appropriate.

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

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

The description uses specific verbs 'Create, change, pause or delete' and identifies the resource as 'standing rule', clearly distinguishing it from siblings like put_proposal and add_item. The scope is immediately clear.

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

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

Explicitly states 'Use this only when the user asks you directly' and provides an example ('stop suggesting PTO stuff'). It also names the alternative tool for scheduled runs (put_proposal) and explains why, making the usage boundary unambiguous.

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: it discloses that the operation replaces the entire previous proposal, that nothing reaches the list until the user accepts it, and that there is a 100-delta cap. This goes beyond the tool name and provides key behavioral expectations.

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?

Three sentences, front-loaded with the core purpose, and every sentence earns its place by adding replacement semantics, safety behavior, and the delta limit. No filler or 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 complex tool with a large schema, the description gives the essential high-level context: replacement, pending review, exclusivity to scheduled runs, and the 100-delta cap. The schema handles parameter details, and the lack of an output schema means return values are not explained, but the description is sufficient for correct selection and 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 100%, so the extensive inline descriptions already explain all parameters. The description adds only a general 'up to 100 deltas' constraint and the advice to include everything worth suggesting, which is marginal value beyond the schema's own delta description.

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

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

The description uses a specific verb and resource: 'Replace the pending set of suggested changes.' It clearly distinguishes itself from siblings by emphasizing that this is the ONLY write the scheduled run should make and that changes are pending until user review, unlike add_item or complete_item which act directly.

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 states clear usage context: 'This is the ONLY write the scheduled run should make' and explains that the proposal replaces any previous one wholesale with a 100-delta limit. It does not explicitly name alternatives, but the scheduled-run context and replacement behavior imply when this tool is appropriate versus the individual sibling tools.

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