Postlia

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

With no annotations, the description carries full burden but only states the primitive action. It does not disclose whether cancellation is destructive, reversible, or requires specific permissions. Effects on related data are omitted.

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 wasted words. It is concise but could include more contextual information without becoming verbose.

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?

Despite low complexity, the description lacks essential context: no mention of return value, success/error behavior, or what to do if the scheduled post does not exist. The output schema is absent, but that doesn't justify the omission.

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 0%, so the description must add meaning. It says 'by id' but does not explain what 'id' refers to (e.g., post id or scheduled post id) or how to obtain it. No additional details 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 explicitly states the action (cancel) and the resource (scheduled post) with the key parameter (by id). It clearly distinguishes from siblings: create_post, list_accounts, list_scheduled_posts.

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?

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing the post to be in a scheduled state, or what happens if the id is invalid.

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 discloses a key behavioral trait (does not spend posting quota), which adds useful context. However, it doesn't mention other behaviors like validation, authentication, or failure semantics, leaving some 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?

The description is one short, front-loaded sentence: 'Save a draft for later without spending posting quota.' Every word earns its place, with no redundancy or unnecessary detail.

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 two-parameter tool without an output schema, the description captures the core purpose and a key behavioral constraint. It lacks context about what happens after saving (e.g., where drafts go, how to publish later) and doesn't describe return values, but it's minimally complete for basic 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 50%: platforms has an example, content does not. The description doesn't explain parameters beyond the tool's purpose. Content is self-explanatory, and platforms is documented, so the description adds minimal value but doesn't need to compensate heavily.

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 ('Save') and resource ('a draft'), with a clear purpose ('for later') and a key differentiator ('without spending posting quota'). This distinguishes it from sibling tools like create_post, which presumably posts immediately.

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 to use this tool: when you want to save something for later rather than publish immediately, avoiding posting quota. It doesn't explicitly name alternatives or exclusions, but the context is clear given sibling tools.

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 important behavioral traits: immediate posting (~5 min), scheduling, queueing, and media prerequisites. It doesn't cover output behavior or potential side effects like rate limits or irreversibility, but the mentioned timing and preconditions are valuable context.

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 cover a 12-parameter tool with conditional logic and platform-specific requirements. Every sentence adds load-bearing information, with the most important verb-first phrasing at the beginning. No redundancy or fluff.

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 complex tool with no output schema and no annotations, the description covers scheduling modes, media prerequisites, and platform-specific options well. It does not mention the return value or how to handle partial failures, and some parameters like platformContent and mediaAlts are left to schema descriptions. Given the 75% schema coverage, this is a solid but not exhaustive effort.

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 adds significant meaning beyond the schema: it explains the exact semantics of scheduledAt, queue, and the mediaUrl/mediaUrls dependency on upload_media. It also clarifies that tiktok/pinterest/youtube require their respective options objects, which ties multiple parameters together. This goes well beyond the schema's individual property 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?

The description opens with 'Create a post', using a clear verb and resource. It goes on to enumerate scheduling modes and media platform requirements, which gives a concrete sense of scope. However, it does not explicitly differentiate from the sibling tool create_draft, 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?

The description provides explicit conditional guidance for when to use scheduledAt, queue, and neither, plus requirements for media platforms. This is strong usage context. It doesn't explicitly mention when not to use this tool or point to alternatives like create_draft, so it doesn't reach 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?

Since no annotations are provided, the description must carry the full burden of behavioral disclosure. It only states the action without revealing whether deletion is permanent, reversible, or has side effects, nor does it mention required permissions or state constraints for the draft.

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 sentence, 'Delete a draft by id.', containing eleven words with no redundancy. It is front-loaded and perfectly sized for a simple delete operation.

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 destructive mutation tool with no annotations, no output schema, and minimal parameter details, the description falls short. It does not explain the consequences of deletion, error conditions, or the expected response, leaving the agent with insufficient context for reliable 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?

With schema description coverage at 0%, the description must add meaning to the sole 'id' parameter. It only says 'by id', which clarifies that the id refers to the draft, but it does not provide format, constraints, or instructions on how to obtain the id, offering minimal added value.

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 action 'Delete' and the resource 'a draft', with the method 'by id'. This verb+resource combination distinguishes it from sibling tools like create_draft, list_drafts, and cancel_post, making the 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 gives no guidance on when to use this tool versus alternatives such as cancel_post or update_post_content. It does not mention prerequisites, conditions, or exclusions, leaving the agent to infer context from the name alone.

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 discloses what information is returned (totals, counts, per-platform volume, errors) but does not explicitly state that this is a read-only operation, nor does it mention any rate limits or data-gathering side effects. The behavior is inferable but not fully transparent.

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, tightly packed sentence that leads with the core purpose and lists the key output components. Every word earns its place; there is no fluff or redundancy.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description adequately specifies what the summary includes. It could mention the time window's timezone or inclusiveness, but for a lightweight analytics tool, this is sufficient. The absence of an output schema is mitigated by listing the result components.

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 'days' parameter. The description merely echoes 'over the last N days' without adding new semantic detail beyond the schema's 'Window in days (1-90, default 30)'. Baseline of 3 applies as no additional parameter insight is provided.

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 ('Post-outcome summary') and enumerates the exact metrics included: totals, published/partial/failed counts, per-platform volume, and recent platform errors. This clearly differentiates it from sibling tools like get_queue_info or list_published_posts, which focus on operational lists rather than aggregated 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 implies the tool is for viewing aggregated post results over a time window, but it does not explicitly state when to use this versus alternatives, nor does it provide exclusions or prerequisites. The context is clear enough, but there is no comparative 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, the description carries the full burden of behavioral disclosure. It conveys that the returned quota is the enforced one and implies a read-only, non-error-prone operation by recommending it as a pre-composition check. However, it doesn't mention permissions or side effects, though these are unlikely for a quota getter.

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 concise sentences. The first sentence states exactly what is returned, and the second provides actionable usage guidance. No wasted words.

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?

Given the lack of parameters and annotations, and the simplicity of the tool, the description is fully adequate. It explains the output fields, the enforcement aspect, and the recommended timing. It complements the sibling list by making it clear this is the quota-checking 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?

The tool has zero parameters, so the schema covers everything. The description adds context about what the quota includes, which helps the agent understand the output even though no parameters need explaining.

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 returns the enforced posting quota, including specific fields (tier, used, limit, remaining). It distinguishes itself from sibling tools by focusing on quota rather than post management, and the reference to batch composition clarifies its unique role.

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 explicitly advises checking this tool before composing a batch, and warns against discovering the limit via errors. This provides a clear 'when to use' and 'when not to use' (don't wait for errors), which effectively guides the agent in choosing 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?

With no annotations provided, the description carries the full burden. It discloses the type of output (per-platform outcome, platform post ids, real error text) and indicates the verification behavior. It does not explicitly state side-effects, but 'get' and 'receipt' imply a non-mutating read, and the described statuses add transparency beyond a generic 'get by id'.

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 front-loaded: the first sentence immediately states what the tool returns, the second sentence states its purpose, and the last sentence clarifies parameter provenance. No wasted words 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 simple one-parameter read tool with no output schema, the description fully covers what it does, why to use it, what to expect, and how to obtain the required id. It leaves no major gaps for an agent to understand invocation and outcome.

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%, describing the id as 'Post id (scheduled or published)'. The description adds source-of-truth context ('Accepts the id from create_post or from list_published_posts'), which is a meaningful semantic enrichment beyond the schema's basic definition.

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 defines the tool's purpose: obtaining a delivery receipt showing per-platform outcome, platform post IDs, and real error text. It uses specific verbs and resource scope ('Delivery receipt for a post') and distinguishes from siblings like get_analytics_summary by emphasizing verification of whether a post went live.

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 explicit guidance on when to use this tool ('Use this to VERIFY a post actually went live instead of assuming') and notes the id can come from create_post or list_published_posts. It does not explicitly mention exclusions or alternatives, but the context is clear enough for an agent to select it over other read/list tools.

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 disclosure burden. It clearly explains what information is returned (schedule and next queue slots) and their interpretation. It does not mention side effects, but this is a read-only info tool, and the description is sufficient.

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, well-structured sentence that front-loads the core content and adds a clarifying example. No wasted words.

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?

Given there are no parameters and no output schema, the description fully explains what the tool returns and its significance. It's complete for the tool's simplicity.

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, so the baseline is 4. The description appropriately adds no parameter information since none exist.

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 provides the posting schedule (timezone + weekly slots) and the next open queue slots, with an explicit tie to when a queued post would publish. This distinguishes it from siblings like list_scheduled_posts or get_posting_quota.

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 to use this tool by referencing 'create_post with queue=true', which tells the agent this is useful for planning queued posts. It doesn't explicitly state alternatives or exclusions, but the context 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?

No annotations exist, so the description carries full burden. It describes a safe read operation ('list') but offers no additional behavioral details such as pagination, ordering, or rate limits. For a parameterless tool, this is adequate.

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, concise sentence that clearly conveys the tool's purpose with no unnecessary words.

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?

Given the tool has no parameters, no output schema, and no annotations, the description provides sufficient information to understand the tool's function. It is complete for a simple list operation.

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 are zero parameters, so the description does not need to provide parameter-level detail. Baseline score of 4 applies per guidelines.

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 explicitly states the verb 'list' and the resource 'connected social accounts', and specifies the context 'on this Postlia workspace'. It clearly distinguishes from sibling tools which deal with posts.

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 when the user needs to see connected social accounts, but does not explicitly say when to use vs alternatives. However, sibling names like 'cancel_post' and 'create_post' make the distinction 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. It discloses two important behavioral traits: the tool excludes scheduled posts and incurs no quota cost. This goes beyond a simple read operation, providing account-relevant context. However, it doesn't mention return format or ordering, leaving some 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?

The description is a single sentence with no wasted words. It front-loads the primary action and adds essential differentiators in a compact parenthetical. Every word 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?

Given the tool's simplicity (no parameters, no output schema, single resource), the description adequately covers purpose, scope, and cost characteristics. The sibling context further clarifies its role among related 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?

The tool has zero parameters, so the schema fully covers the input space. The baseline for no parameters is 4, and the description adds no parameter-specific detail, which is appropriate since there is nothing to clarify.

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 'List' with resource 'saved drafts' and explicitly differentiates from scheduled posts and quota implications. This clearly distinguishes the tool from siblings like list_scheduled_posts and get_posting_quota.

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 phrase 'not scheduled, cost no quota' provides clear context on when to use this tool—when you want drafts rather than scheduled posts and when quota cost is a concern. It implies alternatives (e.g., list_scheduled_posts) but does not explicitly name them, so it falls short of a perfect score.

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 must carry full behavioral transparency burden. It discloses that results include per-post outcome status and any platform errors, which is useful, but it does not mention that this is a read-only operation, require authentication, or note any side effects or limitations. The description is too minimal to adequately convey behavioral traits.

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 sentence with no wasted words. It is front-loaded with the core concept and immediately conveys the tool's purpose. Every word earns its place, achieving high 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?

For a simple list tool with one parameter and no output schema, the description covers the essential output ('post history with outcome status and any platform errors') but lacks details such as ordering, filtering, or what 'recent' means exactly. It is minimally viable but incomplete in helping an agent fully understand the tool's behavior and 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?

The single parameter 'limit' is already fully described in the schema with type, range, and default (1-50, default 20). Schema coverage is 100%, so the description adds no value beyond the schema. Baseline 3 applies because the schema handles the parameter semantics completely.

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 'Recent post history with per-post outcome status and any platform errors' clearly implies listing published posts with status/error details, distinguishing it from siblings like list_drafts and list_scheduled_posts. However, 'recent post history' is a bit vague and does not explicitly state it returns a list, relying on the tool name for the verb.

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 does not provide any guidance on when to use this tool versus alternatives such as list_drafts or get_post_receipt. It implies usage for checking recent posting status, but there are no explicit exclusions or contextual cues about when to choose one tool over another.

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, and the description does not disclose behavioral traits such as whether the tool is read-only, requires authentication, or returns full data. It simply restates the tool's name without adding extra context.

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 sentence, front-loaded, and contains no unnecessary words. It is concise and to the point.

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 with no parameters, but the description could be more complete by explaining what 'upcoming' means (e.g., based on publish time) and whether results are ordered. Without an output schema, the agent lacks full context on what the tool returns.

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 are no parameters, so the input schema covers everything vacuously. The description does not add parameter info, but with 0 parameters, the baseline of 4 is appropriate since there's nothing to clarify.

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 'List upcoming scheduled posts' clearly states the verb (list) and resource (scheduled posts), with 'upcoming' distinguishing from possibly past posts. It is not a tautology and effectively differentiates from sibling tools like create_post or cancel_post.

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?

No guidance is provided on when to use this tool vs alternatives. For example, it does not mention that this tool is read-only or that create_post should be used for creating posts. The description lacks context for decision-making.

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 provides some constraints (pending scheduled post, future time, ISO datetime) but does not mention side effects, permissions, error handling, or the outcome of the operation, resulting in partial transparency.

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, well-structured sentence that is direct and free of unnecessary detail. It is appropriately sized for the tool's simplicity.

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?

Despite the simple schema and lack of annotations, the description omits important context such as what happens if the post is not pending, what the response indicates, or any prerequisites. It is minimally adequate but lacks completeness for a tool with no output schema or annotation support.

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 input schema only defines types for id and scheduledAt with no descriptions. The description clarifies scheduledAt as an ISO datetime for a future time and implies id refers to a pending scheduled post, adding meaningful semantics 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 clearly states the action ('Move') and the resource ('pending scheduled post'), and specifies the target state ('new future time (ISO datetime)'). This distinguishes it from sibling tools like cancel_post and update_post_content.

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 no explicit guidance on when to use this tool versus alternatives. It lacks mentions of prerequisites, exclusions, or references to other tools, leaving the agent to infer usage 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 provided, the description must carry the full burden of behavioral disclosure. It only mentions that platform character limits are enforced, but does not state whether the operation overwrites existing text irreversibly, requires specific permissions, or what happens if the post is not in a pending scheduled state.

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 short sentences, front-loaded with the primary action. Every word earns its place, with no unnecessary 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 simple two-parameter update operation, the description conveys the core action and a key constraint, but lacks details on return behavior, prerequisites, or error cases. It is adequate but leaves notable gaps given the lack of annotations and output 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 0%, so the description must compensate. It refers to 'text' which maps to the 'content' parameter, giving some hint about its meaning, but does not explicitly explain 'id' or provide format/encoding details. It adds partial value beyond the bare 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 uses a specific verb ('Rewrite') and resource ('pending scheduled post's text'), clearly distinguishing this from sibling tools like create_post or cancel_post. It leaves 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?

The phrase 'pending scheduled post' clearly delimits when this tool should be used: only for scheduled posts that have not yet gone live. This implies it is not for drafts or published posts, providing clear context without explicitly naming alternatives.

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 discloses that the tool pulls from a public URL, returns a storage URL and media type, supports a specific set of formats, and enforces a size limit. This goes beyond a simple 'upload media' statement and provides meaningful behavioral context, though it omits potential error conditions.

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, front-loaded with the main action and purpose. It efficiently conveys the operation, return value, integration point, and key constraints without redundant 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 tool with a single parameter and no output schema, the description provides complete information: what it does, what constraints apply, what is returned, and how it fits into the workflow (create_post). No annotations or additional structure leaves 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?

The schema covers the only parameter (url) with a basic description. The description adds value by explaining what type of content is expected (image or video), listing supported formats, and indicating the size limit, which clarifies the URL's content requirements 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 clearly identifies the tool's purpose with a specific verb ('Pull') and resource ('image or video from a public https URL into Postlia storage'). It distinguishes itself from all sibling tools, which focus on posting and drafts, not media ingestion.

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 a clear use case ('ready for create_post') and specifies constraints (public HTTPS, supported formats, max 25 MB). It doesn't explicitly name alternative tools, but no sibling upload tool exists, so the context is sufficient.

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