Platemark

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

With no annotations, the description carries the full behavioral burden. It implies a non-mutating introspection of the connected key's quota, which signals a safe read, but it does not confirm read-only semantics, state what happens with an invalid or expired key, or indicate whether results are cached or live.

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 key concept (plan and credits) is front-loaded. The phrasing "credits left" is slightly informal but costs nothing in length.

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 zero-parameter read tool this is close to adequate, but with no output schema the description is the only guide to the return payload, and "plan and credits left" omits units, currency, expiry/reset timing, and whether limits are per-key or per-account.

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 there is no parameter semantics to explain and the schema itself is complete. The description correctly adds no parameter talk, matching the empty input object.

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?

"Plan and credits left for the connected key" names the resource content being reported, so an agent can infer this returns billing/quota status. But it is a noun phrase with no verb (get/read/retrieve) and never says it returns a status object for the currently authenticated key, leaving the purpose only implied.

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 no when-to-use guidance, no prerequisites, and no routing versus the siblings (create_account, list_templates, render_image). An agent must guess whether this is for pre-flight quota checks, post-failure diagnosis, or account setup.

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?

Without annotations, the description carries the behavioral burden well: it discloses plan limits (100 images/month, watermark), that the API key is shown only once, and that it must be added to the server's Authorization header. It omits duplicate-email/idempotency behavior and error handling, so it is not fully complete.

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 compact sentences, front-loaded with the action and plan limits; the one-time key instruction is critical and earns its place. No filler.

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 single-parameter account-creation tool with no annotations or output schema, the description covers plan constraints, return value, and the critical auth-header next step. It leaves gaps around duplicate accounts and email semantics, but is close to 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 has one required parameter with 0% description coverage, so the description must explain it. It never mentions email—e.g., whether it is the login identifier, must be unique, or triggers verification—so it adds no meaning beyond the schema's type.

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 (create) and resource (Platemark account), and adds the account tier and return value (API key). An agent can distinguish it from account_status, which checks status rather than creating an account.

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?

Implies use when a user lacks an account but does not explicitly state when to use it versus account_status or what to do for an existing account. No exclusions or prerequisite guidance beyond the free plan details.

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 burden. 'List' implies a non-mutating read and the sentence discloses the returned fields (size, slots), but it says nothing about auth requirements, pagination, ordering, or list size. Adequate for a low-risk read, but not rich 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?

Two short sentences, the purpose is front-loaded, and the second sentence carries actionable sequencing guidance. Nothing is redundant or padded.

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-optional-parameter read tool with no output schema, the description covers what is returned and when to call it, which is enough to invoke correctly. Only minor gaps remain, such as whether results are paginated or ordered.

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 description never mentions the optional 'tag' parameter, so it adds no meaning beyond the schema. However, schema description coverage is 100% and the parameter's own description already explains the filter with concrete examples, 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?

States a specific verb and resource ('List Platemark image templates') plus the payload the caller gets back ('size and the slots each one takes'). That is clearly distinct from the sibling tools account_status, create_account and render_image, so an agent can select it without opening the schema.

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?

'Call this first to pick a template and see slot names' gives explicit ordering guidance, implicitly positioning it ahead of render_image. It stops short of stating when not to use it or how the optional tag filter changes selection, so it is strong context rather than a full when/when-not rule set.

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 returned format, auto-shrink text behavior, accepted image formats and size ceiling, slot-omission semantics, and a billing cost. It omits error behavior, auth requirements, and how/where the PNG is delivered (URL vs binary), which are the remaining behavioral gaps.

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?

Five short sentences, front-loaded with the outcome, then constraints, then cost. Every sentence adds a distinct fact and nothing is repeated from the schema or padding.

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 output schema exists, and the description compensates by naming the return artifact (finished PNG) and the slot-merging behavior. For a two-parameter tool with a nested modifications object this is nearly sufficient, with the delivery mechanism of the PNG being the main unexplained element.

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 baseline is 3, but the description adds real meaning beyond the schema: that percentages are not needed for text (it shrinks to fit), that image values must be https and under 4 MB, and that omitting a slot preserves the sample. That goes beyond the schema's brief 'a value is a string or an object' wording.

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?

"Fill a template's slots and get back a finished PNG" gives a specific verb (fill), resource (template slots) and output artifact (PNG), so the agent knows exactly what the call produces. It never names the sibling list_templates as the source of template ids, so the differentiation with siblings rests on the schema rather than the description.

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?

Useful operating rules are present (omit a slot to keep its sample, image slots require https PNG/JPG/GIF under 4 MB) and the 1-credit cost informs cost-benefit decisions. However, there is no explicit guidance on when to call this versus list_templates first or when not to call it, so usage is implied rather than stated.

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