ShareCut QR & Short Links

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

No annotations are present, so the description carries the burden. It adds useful operational context: the tool is FREE, requires no API key, and is a non-mutating availability check rather than a claim action. It does not describe the exact response when a code is unavailable, but the read-only nature 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?

Three short sentences with no filler. Operational context and usage come first, format constraints last, and every sentence contributes useful 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?

For a one-parameter tool with no output schema, the description covers purpose, usage timing, input constraints, and cost/auth. The main gap is the exact return signal when the code is not free, but this is minor for an availability-check tool.

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% and includes an example. The description adds value beyond the schema by specifying accepted characters and length: lowercase letters, digits, hyphens, up to 10 characters, which helps avoid invalid calls.

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: 'Check whether a custom short code is still free'. It also refers to shorten_url as the follow-up action, distinguishing this preflight check from the claiming tool and other link-management siblings.

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 positions the tool as a precondition: use it 'before trying to claim it with shorten_url'. It does not enumerate when not to use it or compare against other siblings, but the intended workflow is clear.

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 delivers: it discloses auth requirements ('no API key needed'), output formats (SVG plus optional PNG data URL), and the critical behavioral trait that the QR is static and immutable once created. It even explains scan-counting consequences when comparing to the dynamic alternative.

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 dense sentences, with the most important facts (free, no auth, output format) front-loaded and the alternative/use condition in a compact second half. No filler or repetition of schema fields.

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 low-complexity tool with 3 simple parameters and no output schema, the description plus schema fully cover what an agent needs: input, output, auth, and the key immutability constraint. The sibling-scoped alternative completes the decision 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?

Schema description coverage is 100%, so the baseline is 3; the schema already explains data, color, and format. The description reinforces the format behavior ('optionally also as a PNG data URL') and the data meaning but adds no significant detail beyond the 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?

The description opens with a clear action: 'Render any URL or text as a QR code and return it as SVG,' naming both the resource and the output format. It also differentiates the tool by labeling this QR as STATIC with a baked-in destination, setting it apart from dynamic alternatives like shorten_url.

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 not to use this tool: if the destination might change, use shorten_url instead, with update_link called out for later edits. This gives an agent a concrete decision rule rather than leaving alternatives to inference.

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 of behavioral disclosure. It discloses irreversibility, cascading breakage of QR codes and shared copies, short-code release, and explicitly notes there is no undo, plus the access/auth constraint.

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?

Every sentence earns its place: destructive effect, cascading impact, irreversibility, preferred alternative, and access requirement. The core action is front-loaded, and there is no filler 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 two-parameter destructive tool with no annotations and no output schema, the description covers the operation's effect, side effects, permissions, irreversibility, and the correct alternative. Nothing essential for selecting or invoking the tool is missing.

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%, with both link and confirm already well described. The tool description adds behavioral context but no additional parameter-level meaning, so the baseline of 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 opens with a specific verb and object — 'Permanently delete a link and its click history' — and follows with concrete effects: QR codes and shared copies stop working and the short code is released. It clearly distinguishes the tool from update_link, the nearest sibling alternative.

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 the agent to prefer update_link when the goal is to send the link somewhere else, which is a clear when-not-to-use signal. It also states the API key and Business plan requirement, giving the agent actionable conditions for invocation.

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 usefully discloses that the tool is 'FREE, no API key needed,' that it resolves links 'without opening it,' and that it only supports ShareCut links. This gives an agent a solid safety and scope picture, though it does not describe rate limits or detailed output behavior.

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 compact and well-structured: it leads with the most operationally important facts (free, no key), states the core behavior, gives a practical use case, and ends with a scope limitation. Every sentence adds value and there is no redundancy or 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 tool with no output schema, the description conveys what the tool returns conceptually — the destination and usage count — and covers authentication and scope. It does not specify error behavior or exact response format, but the core usage context is sufficiently complete for correct 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?

The schema already fully documents the single parameter, including that shortCode can be 'The short code, or a full https://sharecut.site/... URL.' The description adds no further parameter-specific meaning, so the baseline score of 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 clearly states a specific action — resolving where a sharecut.site short link goes and how many times it has been used — with a clear resource and scope. It does not explicitly compare itself to sibling tools such as check_short_code or get_link, but the stated purpose is specific enough to distinguish itself functionally.

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 a concrete use case: 'Useful before following or forwarding a link someone sent.' It also provides an exclusion with 'Only resolves ShareCut links.' However, it does not mention alternatives or when not to use this tool in favor of a sibling, so it falls short of fully explicit 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 provided, the description carries the full burden. It openly declares that the operation is a read ('Read'), mentions the authentication requirement, and specifies what data is returned. It doesn't detail response format or edge cases, but for a simple no-parameter getter this is solid 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 two sentences and contains no filler. The first sentence packs a lot of detail into a long clause, but every piece is useful, and the second sentence adds concrete usage guidance.

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 read-only, no-parameter tool, the description covers what it does, when to call it, and what prerequisite is needed. It doesn't enumerate response format or error behavior, but it is otherwise complete for an agent selecting and invoking it.

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 has zero parameters and schema coverage is 100%, so there are no parameter gaps. The description adds useful context by explaining that the implicit subject is the current API key's account, which clarifies what the empty input schema means.

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 identifies a specific verb ('Read') and resource ('plan behind the API key', quota, link counts), and the scope is account-level, distinguishing it from all link/QR-focused siblings. It directly explains what information is returned, leaving no ambiguity about the tool's function.

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 practical guidance: 'Worth calling before a bulk run' and states a prerequisite ('Requires a ShareCut API key (Business plan)'). It doesn't list exclusions or alternative tools, but no account-level sibling exists, so this is sufficient context.

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. It discloses that the operation is a read (non-destructive) and lists the returned fields, which is useful behavioral information. However, it does not address rate limits, failure modes, or any side effects, and the auth requirement is a prerequisite rather than a behavior. This is adequate for a simple read but not rich.

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 with zero waste. The core action is front-loaded ('Read one link'), followed by a concise list of returned fields, then a single prerequisite. No filler or redundant phrasing.

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 read tool with no output schema, the description sufficiently covers what is returned (by listing fields) and the auth requirement. It doesn't describe the output shape or error cases, but given the simplicity and full schema coverage, it is almost complete; a minor gap on error behavior keeps it from a 5.

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 parameter's description already explains the accepted formats (short code, id, or full URL). The tool description adds no extra parameter semantics, 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 specific action ('Read one link') and a clear resource, then enumerates the exact fields returned (destination, title, click count, creation date, UTM settings). This distinguishes it from siblings like list_links (lists many) and get_link_analytics (analytics focus), leaving no doubt about what the tool does.

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 mentions a hard prerequisite (ShareCut API key, Business plan) which gives some usage context, but it offers no explicit guidance on when to choose this over alternatives like list_links or get_link_analytics. The phrasing 'Read one link' implies you want a specific link, but the distinction is left to inference.

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 behavioral disclosure burden. It openly states this is a read operation, lists the returned data elements, and discloses the API key/Business plan requirement. It does not cover rate limits or error behavior, but it gives enough for a safe read-only call.

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, no fluff, and the core purpose is front-loaded. The second sentence adds a necessary access prerequisite. Every part is useful.

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 schema covers parameter details and defaults, while the description explains what the call returns and the access requirement. Given the low complexity and lack of output schema, this is complete enough for an agent to use correctly, though error behavior and output formatting are not described.

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 schema already fully documents both parameters. The description adds only the context that analytics apply to 'one link', which reinforces the link parameter but does not add meaning beyond the 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?

The description gives a specific verb ('Read') and a clear resource ('click analytics of one link'), and it enumerates the exact metrics returned. This distinguishes it from generic link tools like get_link or list_links, so the agent knows precisely what this tool does.

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 clearly implies when to use the tool: whenever click analytics for a single link are needed. It also provides an explicit prerequisite (ShareCut API key on the Business plan), though it does not name alternatives or exclusion conditions.

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 behavioral disclosure burden. It does well by revealing that saved artwork is returned when present, otherwise a plain code is rendered, and by disclosing the API key and plan requirement. It does not describe the exact return transport, but the behavior is substantially transparent for a read-only fetch 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?

The description is three sentences with no filler. It front-loads the core purpose, explains the conditional behavior in the second sentence, and closes with the access requirement. 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?

The definition covers the main behavioral variants, auth requirements, and the meaning of 'plain' versus saved artwork. Since there is no output schema, it would be slightly stronger if it stated the exact return format, but the wording 'QR code ... ready to print' and the format parameter sufficiently imply the result for typical use.

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 schema already documents every parameter clearly. The description adds useful context about stored artwork, frames, colours, and logos, but it does not need to add parameter-level meaning and does not go significantly beyond the 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?

The description opens with a specific verb and resource, 'Fetch the QR code for an existing link', and clearly distinguishes itself from sibling tools like create_qr by emphasizing 'existing link'. It also explains the two possible result modes, stored artwork or plain code, which removes ambiguity about what the tool returns.

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 implies usage context: use it when you have an existing link and need a print-ready QR code, and it warns about the Business plan requirement. However, it does not explicitly name alternatives such as create_qr or state when this tool should not be used, leaving the routing decision mostly to inference.

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 of behavioral disclosure. It discloses the authentication requirement (Business plan API key) and the data scope (links with click counts). It implies a read-only operation via the verb 'list,' and describes filtering/sorting capabilities. However, it does not explicitly state that the operation is non-mutating, nor mention rate limits or response pagination behavior, which are minor gaps given the simplicity of the 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?

The description is two sentences with no filler. The first sentence front-loads the primary purpose and scope, and the second sentence efficiently covers filtering, sorting, and the authentication requirement. Every word earns its place, making it highly concise and well-structured.

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 list operation with 5 optional parameters and no output schema, the description adequately conveys the core behavior: it returns links of the specified types with their click counts, and supports filtering and sorting. It does not explicitly describe the response shape, but the mention of click counts and link types gives a sufficient hint. Given the simplicity of the tool and the absence of an output schema, this is reasonably complete; the only minor gap is not mentioning pagination behavior, though offset/limit are in the 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 description coverage is 100%, so the baseline is 3. The description adds some context by mapping 'filter by type or search term' to 'type' and 'q', and 'sort by newest or most clicked' to 'sort', but these details are already fully described in the schema enums. It does not add significantly new meaning beyond what the parameter descriptions already provide, so a 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 clearly states the tool 'lists the links on the account the API key belongs to,' specifying three distinct link types (short links, link-in-bio pages, restaurant menus) and that click counts are included. This is a specific verb-resource combination that clearly distinguishes it from siblings like get_link (single link) or get_link_analytics (analytics).

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 provides clear context for when to use the tool (listing all account links) and includes a prerequisite (requires a ShareCut API key on a Business plan). While it does not explicitly name alternatives or exclusions, the context is sufficient for an agent to distinguish it from sibling tools. The lack of explicit 'when not to use' guidance prevents a 5.

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 delivers: it discloses the Business-plan API key requirement, Google Web Risk destination screening, dynamic QR behavior, and per-scan tracking of country/device/referrer. It omits error/rate-limit behavior, but the notable operational 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?

Four compact sentences, front-loaded with the core action and outcome, then moving to differentiators, screening, and auth. No filler, though the QR/analytics aside is slightly dense for a single sentence.

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 mutation tool with no annotations and no output schema, the description covers what is produced (short link plus QR), who can call it (Business-plan key), and the screening/tracking side effects. Only failure modes and any reversibility details remain unstated.

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 schema already documents url, utm, title, and customCode thoroughly, including the check_short_code hint. The description adds no parameter-level meaning beyond what the schema provides, so the 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 opens with a specific verb+resource+outcome: create a ShareCut short link for a URL and get a matching QR code. It clearly distinguishes itself from expand_short_link, get_link_qr, and shorten_urls_bulk by naming the single-URL creation behavior and the dynamic-QR capability.

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 explains why to choose this over a static QR and names update_link as the mechanism for post-print edits, giving contextual guidance. It stops short of stating when to prefer shorten_urls_bulk over this tool or any explicit exclusions.

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 burden of behavioral disclosure. It does well by revealing that failures are reported per item, preventing one bad URL from discarding the rest, and noting the API key/plan requirement. It does not describe the exact response shape, but the per-item failure behavior is a meaningful and useful disclosure beyond basic creation.

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 concise sentences, each providing distinct value: the core capability and limit, the field reuse, and the failure isolation behavior. It is front-loaded and contains 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 relatively simple bulk creation tool with a single parameter, the description covers the critical context: limits, plan requirement, field reuse, and partial failure handling. The lack of an output schema is somewhat mitigated by the per-item failure note, but a bit more detail about the response format would make it fully 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 already documents the 'links' array and each nested field (url, title, customCode) with 100% coverage, so the description does not need to repeat them. It does add a useful pointer that each entry takes the same fields as shorten_url, but this only slightly supplements what the schema provides. 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 clearly states a specific action ('Create up to 25 short links in one call') and distinguishes itself from the sibling tool shorten_url by explicitly calling out the bulk behavior. It also communicates key constraints like the 25-link limit and the shared field structure, making the tool's purpose 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?

The description implies when this tool should be used instead of shorten_url: when multiple links need to be created at once. It also gives relevant context about the required ShareCut API key and Business plan. However, it does not explicitly say 'use this instead of shorten_url for batches,' so the routing guidance is good but not fully explicit.

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 so well: it discloses the blast radius of the mutation (every printed/shared copy redirects), that click history is preserved, that the destination is screened with Google Web Risk, and that a ShareCut API key on the Business plan is required. It still omits whether omitted fields are left untouched and what a rejected destination looks like, so not 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?

Front-loaded with the core action, and the QR-code rationale is placed right where it explains the value of updating rather than recreating. The 'stuck on a wall' phrasing is slightly decorative, but every sentence still carries a distinct fact (persistence, validation, auth).

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 mutation tool with no annotations and no output schema, the description covers side effects, auth requirements and validation adequately. It would be fully complete if it stated the partial-update semantics for optional fields and the failure mode when Web Risk blocks a destination.

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 schema already documents all five parameters including the utm off-switch and accepted link formats. The description adds only a restatement of the mutable fields and the short-code immutability rule, which is a baseline-3 contribution.

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 (re-point/change) and resource (existing short link) plus the exact fields that can change, and contrasts implicitly with creation tools like shorten_url by saying the link already exists. An agent can distinguish it from delete_link, create_qr or shorten_url without opening a 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?

Gives clear context for when to use it (making an already-printed QR code reusable) and draws the line at what it does not do (the short code itself never changes here). It never names a sibling tool explicitly, so the agent must infer that shorten_url handles new links, which keeps it short of a 5.

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