b59.link

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

With no annotations, the description carries the full behavioral burden and does well: it discloses the rate-limit change (2 → 300/min), the account-creation side effect for new emails, and the exact session-key transport ('Authorization: Bearer <session_key>'). It does not cover session-key expiry or error cases, which keeps 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 sentences, front-loaded with the payoff and reason to authenticate, then the two credential paths, then the header usage. No filler; each sentence carries distinct information an 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?

No output schema and no annotations, so the description must cover returns and it does (a session key, plus an api_key for newly signed-up emails). Missing only lifecycle details such as session-key expiry or failure behavior, which are secondary for successful 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 coverage is 100%, so per-parameter meaning is already documented; baseline would be 3. The description adds value beyond the schema by explaining the relational, multi-step semantics of the parameters (email → emailed otp → second call with email + otp), which the flat schema cannot express.

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 ('Sign in to b59.link') plus the concrete benefit (rate limit 2→300 req/min, ownership of created resources). This clearly distinguishes it from the sibling tools (shorten_url, make_qr_image, get_stats_url), which are all anonymous content operations.

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 routes between the two flows: pass api_key for an immediate session key, or pass email to receive a 6-digit code and then call again with email + otp. It even discloses the side effect that new emails are signed up and receive an api_key, so an agent knows which path to take without guessing.

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 behavioral burden and does well: it discloses that the tracker is free, that it returns a tag image URL, paste-ready snippets and a stats URL, that ownership follows auth state, and that a manage_token must be kept to claim an anonymous tracker. Missing only secondary traits like rate limits or error 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?

Three tightly packed sentences, front-loaded with the action and then the return values, with no filler. Density is high but every sentence earns its place; slightly long phrasing around the return payload keeps it from a 5.

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?

There is no output schema, so the description correctly compensates by enumerating the return values (tag URL, snippets, stats URL) and the auth/ownership lifecycle including the manage_token. This covers what an agent needs to call and use the tool correctly; only edge cases like errors or token expiry are omitted.

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 both parameters (name, site_url) are already documented in the schema, including the domain/subdomain counting rule. The description adds no parameter-level detail beyond that, 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?

States a specific verb and resource ("Create a free page-view tracker for a website") with clear scope. It distinguishes itself by resource type from siblings like generate_qr or shorten_url, but never names an alternative, so it stops short of full sibling differentiation.

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 rather than stated: the agent can infer this is the tool for creating a tracker, and the signed-in/not-signed-in note hints at account context. There is no explicit when-to-use/when-not or reference to the sibling tools (get_stats_url, lookup_url) that a caller might confuse it with.

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 disclosure burden, and it does the most important part: it reveals that generating a QR code also creates a persistent short URL as a side effect, which the schema does not suggest. It also enumerates the return payload. It stops short of permissions, rate limits, or whether the short URL is permanent/deletable.

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 core action, then the non-obvious side effect, then the return shape. No filler and nothing buried.

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 and no annotations, the description covers the action, the hidden write side effect, and the three return values, which is what an agent needs to call it correctly. Auth requirements and any URL validation rules are the only notable gaps.

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% for the single `url` parameter, whose schema text already says 'The URL to generate a QR code for.' The description restates the same idea without adding format constraints (e.g., fully-qualified URL only), 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 ('Generate a trackable QR code for a URL') and immediately clarifies the coupled side effect of creating a b59.link short URL. The word 'trackable' distinguishes it from the make_qr_image and shorten_url siblings, though it never names them outright, so the differentiation is implied rather than explicit.

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 by the word 'trackable' — an agent can infer this is the choice when scan counting is wanted — but there is no explicit when-to-use statement or comparison against make_qr_image / shorten_url. No exclusions, prerequisites, or preconditions are given.

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 behavioral burden, and it does disclose a meaningful trait: the tool returns a URL pointer, not stats data. It says nothing about permissions, rate limits, or what happens when an identifier is unrecognized, so it is adequate but incomplete.

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 filler, and the scope plus the 'returns where' clarification are front-loaded. Every clause 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 single-parameter tool with no output schema or annotations, the description covers what the tool does, what inputs it accepts, and what it returns. Missing only edge-case behavior such as invalid identifiers or auth requirements.

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 already 100%, so the baseline is 3, but the description adds nuance beyond the schema by clarifying that the identifier may be a destination URL of a short link or QR code, an accepted form the schema entry does not spell out.

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 (stats page URL) and explicitly clarifies that it returns the location rather than the stats themselves ('Stats themselves are viewed on b59.link; this returns where'). This cleanly separates it from siblings like lookup_url and shorten_url, which return data rather than a view 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?

Gives clear context for when it applies ('for anything b59.link tracks') and enumerates the acceptable identifier shapes, which implicitly guides usage. It does not, however, name a sibling alternative or state when not to use this tool.

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. It does add useful behavior beyond the schema: input normalization (http/https, www, trailing slash) and what is returned when a match is found. It does not state what happens on a miss, whether auth is required, or any rate limits.

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, zero filler, and the core purpose is front-loaded before the normalization and return-value details. 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 1-parameter read tool with no output schema and no annotations, the description covers purpose, normalization, and return content well. The only meaningful gap is the not-found / no-match outcome, which the agent would need to know.

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% for the single 'url' parameter, so the baseline is 3. The normalization note hints at how the input is matched, but the description adds no format or syntax detail beyond what the schema already documents.

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 verb (check/lookup) and resource (existing b59.link short URL), which is unambiguous on its own. It implicitly contrasts with the create-style sibling shorten_url, but never names or explicitly rules out siblings such as shorten_url or get_stats_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?

Usage is implied by the description's 'check whether a URL already has a short URL', so an agent can infer this is a pre-shortening / dedupe lookup. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool (e.g., shorten_url when no match exists) is named.

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. It discloses that no short link is created and that the tool returns an image plus a permanent, embeddable image URL, which is useful beyond the schema. It omits details like auth requirements, idempotency, or rate limits, keeping it from 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 compact sentences, front-loaded with the core purpose and scoping constraint. Every sentence adds relevant information with 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?

No output schema exists, so the description must explain returns; it does by stating it returns the image plus a permanent image URL embeddable with <img src>. It could additionally clarify the response shape or auth model, but the core behavior is complete for 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%, so baseline is 3. The description adds semantic value for the 'data' parameter by listing accepted content types (URL, Wi-Fi string, phone, email, plain text) and notes that colors, size, and SVG are supported, which goes beyond the terse schema descriptions.

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 ('Make a QR code image for any text') and explicitly contrasts with the sibling 'generate_qr' for scan counting. An agent can distinguish it from generate_qr without reading either 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 explicit when-to-use guidance: use this tool for QR generation without short links, and use 'generate_qr instead when scans should be counted.' This names the alternative and the exact condition that selects 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?

With no annotations, the description carries the full burden. It does disclose the return values ('Returns the short URL and a stats URL'), which is useful behavioral context. However, it omits any mention of authentication requirements, rate limits, permanence of links, or error behavior, leaving significant 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?

Three short sentences that are front-loaded with the core purpose and contain no filler. The optional slug sentence is somewhat redundant with the schema but does not detract from the efficient structure.

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 tool is simple and the input schema is rich, and the description covers the return values despite no output schema. However, without annotations it should have provided more behavioral context (e.g., authentication, link permanence) to be fully complete for an agent.

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 the url and slug parameters. The description's mention of an optional custom slug adds no meaning beyond what the schema provides, 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?

States a specific verb and resource ('Shorten a long URL') and names the output domain ('b59.link'), making it distinct from siblings like lookup_url or get_stats_url. However, it does not explicitly contrast itself with those siblings, so it falls short of a 5.

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?

Offers no explicit when-to-use guidance or alternatives. The intended use case is implied by the purpose, but nothing tells the agent when to choose this tool over lookup_url or generate_qr. This matches the calibration's 2 for a tool with no usage context.

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