Superbridger free tools

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

The annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds some output cardinality and default medium context, but much of that also appears in the schema, and it does not explain return structure, how existing UTM parameters are handled, 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?

The description is a single front-loaded sentence with no filler. The key action, default medium, and output modes are all presented efficiently.

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 an 8-parameter builder with no output schema, the description plus schema is mostly sufficient: url, tidy, platforms, and defaults are covered by the schema, while the description covers purpose and output cardinality. It still leaves return structure and edge-case behavior implicit, but the annotations reduce the need for further safety disclosure.

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 75%, so the baseline is around 3. The description usefully maps parameter names to UTM tags and indicates that content and term are optional, but it omits tidy and mostly repeats schema-supplied defaults for medium, source, and platforms.

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 and resource: adding utm_source, utm_medium, utm_campaign, and optional utm_content/utm_term to a link. It also clarifies the two output modes: one link per platform or one for a named source.

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 for creating campaign tracking links, but there is no explicit when-to-use or when-not-to-use guidance. The sibling tools are unrelated, so lack of alternative routing is less harmful, but the description still gives no guidance on existing tagged links or 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real behavioral substance: the exact counting models per platform (X weighted 280 with emoji 2 and links 23, TikTok UTF-16 2,200, YouTube 100-char title and 5,000-byte description, hashtag and mention caps) and that it returns counts, limits and a fit verdict.

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, front-loaded with the core action and return value. The parenthetical rule details are dense but each earns its place by explaining platform-specific counting; a slightly more scannable structure would help.

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 output schema, the description carries the burden of explaining the return value, and it does so ('counts, limits and whether it fits'). For a read-only three-parameter tool this is nearly complete, though it never mentions xPremium's effect on the X limit, which the schema covers instead.

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 text, title and xPremium, including the 25,000-character Premium fallback that the description omits. The description's counting rules add context but do not map additional meaning onto specific parameters.

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 ('Counts a post's text') and names the platforms and limits it targets. It is clearly distinguishable from siblings like get_platform_specs because it evaluates a given text rather than listing specs.

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 pre-post validation, but the description never states when to use it versus get_platform_specs or check_video, and offers no exclusions or prerequisites.

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?

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the verdict is derived purely from technical metadata rather than the file itself, and the return value is a per-platform verdict with each check's message, which tells the agent the output is a structured audit rather than a boolean.

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, front-loaded with the purpose and the platform dimension, with the parameter inventory and return shape following. The dense enumeration is efficient rather than padded; no sentence is redundant.

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 does give a rough return shape ('verdict per platform with each check's message'), which is the right thing to include. But for a 13-parameter tool it leaves open which platforms are evaluated, how partial metadata affects verdicts, and whether a pass/fail plus message is the only payload — gaps an agent would want closed.

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?

With 69% schema coverage the schema already documents most parameters, including rotation-aware width/height and codec formats. The description enumerates the same facts in prose (size, length, dimensions, frame rate, codecs, sample rate, container, HDR, fast start), which confirms the model but adds little syntax or format meaning. It also never clarifies that only fileSizeBytes is required and that omitted optional facts likely weaken or skip certain checks.

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 ("Says whether a video will post on each platform") and immediately scopes what 'posting' means (Reel, Short, video, IG/FB Story). That level of specificity separates it cleanly from siblings like check_caption or get_image_sizes without the agent needing to open 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?

Usage is only implied: an agent can infer this is a pre-publish validation step, and the phrase 'from its technical facts' hints that no file upload is involved. However, there is no explicit when-to-use versus when-not guidance, no mention of the alternatives (get_platform_specs, check_caption), and no stated prerequisites or 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile needs no restating. The description contributes one piece of behavioral context beyond that—that each size is returned 'with each size's source'—but says nothing about result volume, ordering, or what happens when data is missing for a platform.

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 front-loaded sentence with no filler, and the returned-content detail is placed where the reader needs it. It is appropriately sized for a trivial single-parameter read tool, though it could have spent a few more words on the platform parameter rather than the parenthetical list.

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 output schema, the description does carry the burden of describing returns, and it does so adequately by naming the size categories and the accompanying source attribution. However, for a lookup tool whose only parameter is undocumented, the definition leaves the agent guessing about default scoping and overlap with sibling reference tools.

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 0% and the single parameter 'platform' is never mentioned in the description at all, so the description adds no meaning beyond the enum values themselves. Crucially, it does not explain the consequence of omitting the optional platform parameter, which is the one semantic gap an agent must resolve before calling.

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 uses a specific verb and resource ('Returns recommended image sizes per platform') and enumerates the asset categories covered (posts, Stories, covers, banners, thumbnails, profile pictures), so the agent knows exactly what content comes back. It does not differentiate from siblings like get_platform_specs or get_safe_zones, which cover adjacent platform-reference territory.

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 when-not-to-use, and no mention of the sibling reference tools (get_platform_specs, get_safe_zones) that an agent could easily confuse this with. The description never says whether calling it without a platform returns all platforms or errors, which is the main usage decision an agent faces.

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?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is the note that each limit carries 'the date they were checked' — a genuinely useful staleness signal for a static reference tool. It stops short of saying whether limits are per-platform objects, how large the payload is, or whether any platform is unsupported, but for a read-only lookup that is a minor omission.

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 that starts with the action and lets the field list do the work; there is no filler or repetition. The dense run-on list of limits is slightly hard to scan but every clause maps to real returned content.

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 output schema, one optional enum parameter, and rich read-only annotations, the description does the necessary work by enumerating return content and flagging the checked date. It is close to complete; only the shape of the returned data and the default behavior when platform is omitted remain under-specified.

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 0%, so the description must carry the only parameter, and it does add partial meaning: the enum members are restated inline and '(or one of them)' conveys that the parameter is optional and that omitting it returns all platforms. The phrasing is ambiguous rather than explicit, and it does not state the default behavior plainly or say what an invalid platform does.

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 ('Returns the limits for posting to Instagram, Facebook, YouTube, TikTok, LinkedIn and X') and enumerates exactly which limits come back (text length and counting rules, hashtags, video length, file size, codecs, frame rate, Stories, posting cadence). That enumeration implicitly distinguishes it from validator siblings like check_caption and check_video, but it never explicitly contrasts with them or with get_image_sizes, which also touches size/shape.

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: the parenthetical '(or one of them)' suggests calling with no platform returns all six and supplying one narrows the result. There is no explicit when-to-use statement, no guidance on pairing it with check_caption/check_video/get_image_sizes (the same limits are presumably the rules those tools enforce), and no when-not-to-use case.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds that results come 'with sources', which is genuinely useful provenance, but it does not say the data is static/hard-coded or what unit the margins are expressed in.

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 filler; each clause (resolution, platforms, what is measured, sourcing) earns its place. It is dense but readable, with only slight cramming at the end.

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 full annotation coverage, the description carries the return-value burden reasonably: it says it returns margins plus where buttons and captions sit, with sources. It could still state the response format or units, which is the only real gap for a zero-arg lookup.

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 nothing the description needs to disambiguate; baseline 4 applies. The description correctly adds no misleading input expectations.

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 names a specific verb and resource — returning safe-zone margins — and pins it to a concrete artifact (1080×1920 vertical video) and a named platform set (Instagram/Facebook Reels, TikTok, YouTube Shorts). That is far more specific than the sibling get_platform_specs, though it never explicitly contrasts itself with that tool.

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 fixed context (vertical short-form video safe zones) rather than stated: there is no 'use this when', no exclusion, and no pointer to the nearby get_platform_specs or get_image_sizes siblings. An agent can infer applicability, but must guess whether specs and safe zones overlap.

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