What Matters

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

With no annotations, the description carries the full burden, and it does well by disclosing the side effect of auto+high (phone notification) and the rationale for reserving it. It does not mention auth, rate limits, or return behavior, but for an add operation, the key behavioral traits are covered.

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 paragraph, front-loaded with the core action, and every sentence adds essential context. No fluff 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?

For a tool with 11 parameters and no output schema, the description nails the most critical behavioral nuances (human vs. auto, review vs. no review). It does not explain return values, but the primary purpose is clear and the schema covers parameter semantics, so it is nearly 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 covers 91% of parameters, so baseline is 3. The description adds meaning beyond the schema by explaining the strategic use of initiated and priority together (e.g., 'auto' with 'high' triggers a phone interruption), which is not evident from enum values alone.

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 distinguishes this tool from the sibling put_proposal by contrasting immediate addition versus scheduled review, 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?

It explicitly states when to use this tool: 'ONLY when the user has just asked for it in conversation.' It also gives a clear alternative: 'Anything found by scanning on a schedule belongs in put_proposal instead,' plus an exception for urgent cases. This is precise 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 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 full burden and satisfies it: it discloses that the tool 'Replaces any previous proposal wholesale,' that it is the only write for the scheduled run, and that changes are gated behind user review ('nothing here reaches the list until the user reviews and accepts it'). It also states the 100-delta limit, covering key behavioral constraints.

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 sentences, front-loaded with the core purpose, and every phrase adds value: the replacement behavior, the exclusive write context, the review gating, and the 100-delta limit. There is zero 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 tool's complexity (multiple delta kinds, rules, parameters) and the absence of annotations or output schema, the description provides essential context: it orients the agent on when to use it, the wholesale replacement semantics, and the critical safety property that nothing reaches the list until user acceptance. The rich schema covers the remaining detail, so the description is complete enough for 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%, and the schema itself provides exhaustive descriptions for all parameters, including the delta kinds, field meanings, and constraints. The tool description adds only a brief contextual note about the 100-delta cap and wholesale replacement, which is already implied by the schema's description of deltas. Per the rubric, a baseline of 3 is appropriate when the schema does the heavy lifting.

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 + resource: 'Replace the pending set of suggested changes.' It clearly distinguishes itself from sibling tools like add_item or complete_item by stating it is 'the ONLY write the scheduled run should make' and that it replaces the entire proposal wholesale, not just a single delta.

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 states when to use: 'This is the ONLY write the scheduled run should make.' It contrasts with alternatives by noting that 'nothing here reaches the list until the user reviews and accepts it,' implying this is for proposing changes rather than direct mutation. It also gives a practical limit: 'up to 100 deltas,' which guides how to prioritize.

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