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

With no annotations supplied, the description carries the full burden. It does disclose real behavior — proportional scaling to 384px width and conversion to monochrome — which is exactly the kind of side effect an agent needs. It omits limits (file size, supported formats), failure behavior, and whether the device must be online, so coverage is 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?

Two short sentences, front-loaded with the action and followed by the practical caveat about image detail. No filler or redundancy, though the closing tip is advisory rather than essential.

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 print tool with an output schema and full schema coverage, the definition covers the action and the key transformation fact. Remaining gaps — size/format limits and device-state prerequisites — are minor but would matter for an agent preparing a real print job.

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 single parameter already documents both accepted forms (absolute local path and data:image base64 URI). The description adds nothing about the image_path parameter itself, so the baseline of 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 states a concrete verb and resource — printing an image to the 咕咕机 device — which naturally distinguishes it from the text/url/mixed siblings by payload type. It does not explicitly name those siblings as alternatives, but the resource specificity leaves little 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 a useful preparatory tip (preprocess high-detail images into a higher-contrast version), but no guidance on when to choose print_image over print_mixed or print_url, and no prerequisites such as confirming device readiness via print_status. Usage is implied by the payload type 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 supplied, so the description carries the full behavioral burden, and it discloses almost nothing beyond the medium: no indication of which printer/device is targeted, whether the job is physically irreversible or consumes paper, what permission or connectivity is required, or what error surfaces on printer failure. The one useful cue is that output lands on a single receipt (implying layout ordering of text and image), but that is thin for an unannotated side-effecting tool.

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 zero padding; the core fact (mixed text+image on one receipt) leads. It is efficient but almost too terse to have any internal structure or prioritization of details.

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?

An output schema exists, so return values need not be explained, and the input schema is fully documented, which covers the mechanical facts. What remains missing is contextual behaviour for a physical print action (device, failure handling, whether repeated calls duplicate receipts) and any routing guidance among the four print_* siblings.

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%, including the key detail that image_path may be left empty to print text only, so the schema already handles parameter meaning. The description adds no format, size, dpi, or placement semantics for the image beyond the fact that both appear on one receipt, so the baseline 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?

"把文字和图片混排打印在同一张小票上" gives a specific verb (打印) plus the combined resource (文字+图片) and the output medium (同一张小票), which is more informative than the bare name. It stops short of naming print_text / print_image as the one-type alternatives, so the distinction is inferable rather than stated.

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 is for the case where both text and an image must appear together, versus the single-type siblings. There is no explicit when-to-use, when-not-to-use, or named alternative, and no note on when to prefer a plain text print.

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 behavioral burden and delivers very little: it does not say whether this is a read-only, side-effect-free operation, whether status is final or transitional, whether repeated polling is expected, or what states can be returned. Only the bare intent of the query is disclosed.

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 short sentence with no filler and the core intent front-loaded. It is efficient, though its brevity borders on under-specification rather than polished conciseness.

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?

An output schema exists and parameter documentation is complete, so return shape and ID semantics need not be repeated. What remains missing, given a status-polling tool, is workflow context such as when to call it relative to the print_* siblings and whether to poll.

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 with 100% schema description coverage ("打印时返回的 Content ID"), so the schema already explains its origin and meaning. The description adds nothing further about the parameter, which is acceptable at the baseline for full-coverage schemas.

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?

"查询一张小票是否已经出纸" states a specific verb (query) and a specific object (whether a receipt has been dispensed), which is clearly a status read rather than a print action. It distinguishes itself implicitly from the print_* siblings through the verb, but never names them or explicitly contrasts the intent.

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 when-to-use guidance: it does not say this should be called after a print_* tool, whether it must be polled repeatedly, or when to stop. The only hint that content_id originates from a prior print call lives in the schema, not the 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 has to carry the full weight of behavioral disclosure, and it delivers the most important trait: text is sent in GBK encoding, and emoji and some rare characters are silently dropped. That silent-loss warning is exactly the kind of context an agent cannot get from the schema, though the description says nothing about device availability or failure behavior for non-encodable input.

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 with zero filler: the action is stated first, and the encoding caveat follows immediately. Every sentence 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 simple one-parameter print tool with an existing output schema, the definition covers the key behavioral risk: losing characters under GBK. Return values need not be explained because the output schema handles them, though device-state or delivery details are absent.

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 the schema already defines the single text parameter; however, the description adds real meaning beyond it by constraining what the text may safely contain. The GBK encoding constraint lets an agent know that some strings will be truncated or dropped when printed.

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 (print a piece of plain text) and a specific target (the Gugu machine), and the word for plain text ('纯文本') implicitly separates this tool from the image, URL, and mixed-content siblings. It does not explicitly name those siblings, so the differentiation needs to be inferred from the noun phrase, not read 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 gives no explicit statement of when to choose this tool over print_image, print_url, or print_mixed. The intended usage can only be inferred from the phrase '纯文本', so an agent must infer the alternative-selection rule instead of being told 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?

No annotations are supplied, so the description carries the full behavioral burden. It discloses the important trait that rendering happens server-side and that certain URL categories fail, which is genuinely useful. It does not describe what happens on fetch failure (error vs blank page), latency, or print sizing, leaving the mutation-side behavior thin.

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, zero filler, and the mechanism is front-loaded ahead of the failure constraint. Every clause 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 one-parameter tool with an output schema, the description covers the essentials: what gets printed, who fetches it, and which URLs are rejected. Only error behavior and latency on failure are left unspecified, a minor gap for a tool this simple.

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 single url parameter is fully documented by the schema (100% coverage), and the description adds real semantics beyond it: the URL must be public-facing and must not require authentication. That constraint meaningfully sharpens how the parameter should be chosen, above the baseline for a fully documented single-parameter 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?

States a specific verb and resource: prints the content of a web page, and notes that the server side fetches and renders it. The siblings (print_text, print_image, print_mixed) make the domain obvious, but the description never names the closest alternative (print_text) to sharpen the boundary. The purpose is nonetheless unmistakable.

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 useful when-not conditions: the URL must be publicly reachable, and intranet addresses or pages requiring login will not print. It never explicitly routes the agent to print_text for plain text or print_image for image URLs, so the guidance is partial (constraints present, alternatives absent).

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