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

With no annotations, the description carries full behavioral burden. It discloses one useful trait (free, i.e. no cost/credit consumed) and that it exercises both auth and network paths, but says nothing about failure modes, latency, or what a result 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?

A single front-loaded sentence with no waste. It is efficient, though the terseness comes partly at the expense of the behavioral detail noted above.

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?

No annotations and no output schema, so the description must explain the result of the check; it does not. An agent knows what the tool tests and that it is free, but not what success or failure looks like on return.

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 takes zero parameters, so per the rubric the baseline is 4. Nothing is missing because there is nothing to describe.

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-plus-resource: checks that the API key and network work. An agent can immediately tell this is a connectivity/auth smoke test. No sibling differentiation is offered, but the siblings (generate_image, get_spending) are far enough away that confusion is unlikely.

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 parenthetical '(free)' implies a use case — validate before invoking paid tools — but the description never states when to call this versus proceeding directly to generate_image or get_spending. Usage is implied rather than specified.

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

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

With no annotations, the description carries the full burden and does well: it discloses the API-key requirement, local persistence, the returned values (file paths and cost), and a cost-scalation warning for 4K/xhigh/max/multi-image runs. It leaves out failure behavior, rate limits, and moderation effects, keeping it short of 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?

Three tight sentences with the capability and output first, the default second, and the cost-disclosure obligation last. Every sentence carries information the agent needs.

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 9-parameter generation tool with no output schema, the description covers the essentials: what is produced, where it goes, what it costs, and the default spec. Gaps remain around mask/reference-image prerequisites and model selection, which an agent would have to infer from the schema alone.

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

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

Schema coverage is 67%, and the description adds meaning only for size and quality by naming the default combo and which settings raise cost. Mask, reference_images, name, model enum, and n receive nothing beyond the schema, so the description is additive but partial.

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 (generate), resource (image), backing model (gpt-image-2.5), auth model (user's own API key), and side effects (saves locally, returns paths and cost). This is clearly distinguishable from the sibling tools check_connection and get_spending.

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?

Gives a concrete default (2K 16:9 + high, ~$0.06) when no spec is requested and instructs the agent to quote cost before doing anything expensive. It does not discuss alternatives or when-not-to-call, but the siblings are unrelated utilities, so the practical guidance is nearly complete.

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 does disclose the returned data (today/month/total spending and an estimated remaining balance), which implies a read-only operation, but it says nothing about freshness of data, currency, or whether the balance figure is an estimate derived from a budget — none of which is knowable elsewhere.

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 sentence with zero waste; the primary action and the returned figures are front-loaded. Nothing could be removed without losing 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?

With no parameters, no output schema, and no annotations, the description is the only source of information — and it does name the values returned. It stops short of clarifying units, currency, or the period boundary semantics, which leaves a small gap for an agent interpreting 'estimated remaining balance'.

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 takes zero parameters, and the description correctly indicates that all figures are returned together rather than selected via an argument. Baseline 4 applies for a no-parameter tool.

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 ('Get') and resource ('spending') plus the scopes covered (today / this month / total, plus estimated remaining balance). Sibling tools (generate_image, check_connection) are unrelated domains, so differentiation is not needed.

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 only implied: an agent can infer this retrieves spending figures, but the description never says when to call it, what preconditions exist, or how the scopes relate (e.g., whether one call returns all three). No alternatives are named, though none of the siblings overlap.

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

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

With no annotations, the description carries the full burden, and it does disclose valuable behavior: a two-phase flow starting with an empty object, intermediate browser instructions, and a success gate ('report success only when the result says synced'). It does not disclose side effects, permissions, reversibility, or what data is transmitted — significant gaps for what appears to be a state-changing 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?

Three short sentences, front-loaded with the trigger condition and sequenced in execution order. Dense and largely waste-free, though 'start with {}' is terse to the point of being cryptic.

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 two-call protocol and success condition are covered, and there is no output schema to explain. But for a 4-parameter, unannotated tool with no safety metadata, the description omits what the sync actually does, what happens on failure, and whether re-invocation is idempotent.

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

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

Schema coverage is 100%, so per-field meaning is handled there. The description adds real value beyond the schema by clarifying that the first call takes no arguments and the second requires all four fields — notable because the schema declares zero required parameters, so without this the agent would not know all four are expected.

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 verb 'sync' and resource 'balance' are named and the trigger phrases distinguish it from siblings like get_spending, but the description never says what is being synced to where or why. The three sentences describe a call protocol rather than the operation's purpose, leaving the actual effect ambiguous.

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 gives explicit invocation triggers ('同步余额' or 'sync my balance'), which is stronger than most definitions. However, it never says when NOT to use it or contrasts it with get_spending, which an agent could plausibly pick for a balance-related request.

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