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

Annotations indicate a mutating but non-destructive operation (readOnlyHint=false, destructiveHint=false). The description adds that the tool saves credentials, which is consistent. However, it does not disclose additional behavioral traits such as side effects, idempotency, or error conditions. No contradiction with annotations.

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 extremely concise, using only two sentences. The first sentence front-loads the critical condition ('after user approves the loginUrl'), and every word serves a purpose.

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 (2 optional params, no output schema), the description covers the core purpose and precondition. It is missing details like expected behavior if called prematurely or what the output might be, but it is still fairly complete for its 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 coverage is 100% with both parameters ('agent' and 'agentId') described in the input schema. The description adds no extra meaning beyond what the schema already provides, so a 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 the tool's purpose: finishing setup after user approval and saving credentials. It uses a specific verb ('finish setup') and resource ('Taisly agent credential'), effectively distinguishing it from the sibling tool 'taisly_agent_setup_start' which initiates setup.

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 tells when to use this tool: after the user approves the loginUrl. It implies the correct sequence relative to 'taisly_agent_setup_start' but does not mention when not to use it or provide alternatives. Still, 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?

The description adds context beyond annotations by specifying the return value (loginUrl) and user action required, but does not elaborate on internal state changes or side effects.

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 concise with two sentences covering purpose and output, no extraneous text.

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 simple tool (2 optional params, no output schema), the description adequately covers purpose, output, and prerequisite, though it could mention error states or default behavior.

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 parameters are already well-described. The description adds no additional meaning beyond what is in the schema, earning a baseline score.

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 initiates browser-based Taisly authentication for an AI agent and returns a loginUrl, distinguishing it from sibling tools like checkin and auth_status.

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 indicates that the loginUrl must be opened and approved before checkin, providing context for when to use this tool, though it lacks explicit 'when not to use' 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?

Annotations already indicate safe, read-only, idempotent behavior. Description adds context about checking validity and counting accounts, which aligns well.

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?

Single sentence, front-loaded, no wasted words. Ideal 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?

For a zero-parameter, read-only tool with no output schema, the description fully covers purpose and result.

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?

No parameters. Baseline 4. Description adds value by explaining what the tool does with its zero-parameter interface.

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?

Description clearly states it checks API key validity and counts social accounts. Specific verb-resource combination. Distinguishes from siblings like taisly_platform_connect_check.

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 versus alternatives. Agent must infer context; no explicit or implicit usage 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?

Annotations declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds that it checks for appearance but does not disclose what happens if the connection hasn't appeared or rate limiting, thus adding some value but not fully comprehensive.

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?

Single sentence of 16 words, directly states the tool's purpose with no extraneous 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 one parameter fully described in schema and no output schema, the description explains the tool's role but does not indicate the return value or behavior (e.g., boolean result, polling interval). This leaves some ambiguity for a check 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?

Schema description coverage is 100% with the platform parameter well-documented. The description adds no extra semantic meaning beyond referencing the start tool, so 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 specifies the verb 'Check' and the resource 'social account connection', and explicitly references the companion tool taisly_platform_connect_start, distinguishing it from 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?

The description implies this tool is used after taisly_platform_connect_start to check if the connection has appeared, providing clear context but lacking explicit when-not-to-use or 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?

Annotations indicate openWorldHint=true and readOnlyHint=false. The description adds value by detailing that the tool returns a connectUrl that requires user browser interaction, which is essential behavioral context beyond the annotations.

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 long, no wasted words. It front-loads the action and clearly states the return value.

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 parameter, no output schema, annotations present), the description covers the purpose, user action, and return value adequately. It could mention the effect of the connection start, but it is sufficient.

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 is only one parameter, 'platform', with 100% schema description coverage. The tool description adds no additional meaning beyond what the schema already provides, so it meets the baseline.

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 verb 'Start browser-based connection' and specifies the resource as 'social account'. It mentions the return of a connectUrl, which distinguishes it from sibling tools like taisly_platform_connect_check that check status.

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 by stating the user must open and approve the URL in the browser, but it does not explicitly provide when to use this tool versus alternatives, nor does it mention any prerequisites or 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and closed-world behavior, so the safety profile is covered. The description adds that the result is per-destination posting constraints, but says nothing about return shape, completeness, caching, or whether unsupported platforms error versus return empty — meaningful gaps for a schema-lookup tool.

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 sentence, front-loaded with the verb and the payload. Nothing is wasted, though the brevity borders on under-specification for a discovery tool whose output matters.

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?

Read-only annotations carry the safety story, but with no output schema the description is the only place an agent could learn what 'constraints and settings' actually contains. It stops short of describing the returned fields or how to consume them before creating a post.

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 the single 'platform' parameter is documented with concrete examples (TikTok, Instagram, YouTube, X, Facebook), so the schema does the heavy lifting. The description adds no additional meaning about accepted values, case sensitivity, or error behavior for unknown 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?

States a specific verb ('Get') and resource ('posting constraints and supported settings' for a destination platform), which is more informative than the title alone. It is distinguishable from taisly_platforms_list, but it never explicitly contrasts itself with taisly_posts_validate, which sounds adjacent in purpose.

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 indication of when to call this versus taisly_platforms_list or taisly_posts_validate, and no mention of the natural workflow (e.g., call before taisly_posts_create to learn required fields). Usage must be inferred entirely from the name.

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 provide readOnlyHint, idempotentHint, and destructiveHint. The description adds no additional behavioral context (e.g., pagination, caching). It meets the baseline but doesn't exceed annotations.

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?

Single sentence with clear verb and object. No wasted words, front-loaded with purpose.

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 parameter-less list tool with full annotations, the description is complete. It specifies the resource (social accounts) and scope (available to this API key).

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?

No parameters exist, so schema coverage is 100%. The description doesn't add parameter info, which is fine given zero parameters. Baseline of 4 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 clearly states the tool lists connected social accounts (TikTok, Instagram, etc.) and distinguishes it from sibling tools like taisly_posts_list or taisly_auth_status.

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 context is clear: use this to see which social accounts are connected to the API key. No explicit exclusions or alternatives are given, but the sibling tool names imply the scope.

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 annotations already declaring non-read-only, non-idempotent, open-world behavior, the description adds critical async semantics: 'success: true means Taisly accepted the request, not that every platform published it.' It also directs the agent to verify per-platform status via taisly_posts_status before reporting success, which is exactly the behavioral nuance an agent needs.

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, zero waste. The confirmation requirement and the success-semantics warning are front-loaded, and the follow-up instruction is stated precisely enough to act on.

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 7-parameter creation tool with nested settings and no output schema, the description covers the two non-obvious risks: user confirmation and async partial success. The remaining parameter details are fully covered by the schema, so nothing critical 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 coverage is 100%, so the schema already documents all seven parameters including nested platform settings. The description reinforces the `confirmed` parameter by saying to call after explicit user confirmation, but it adds little semantic detail about video, platforms, scheduled, or settings beyond what the schema provides.

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: 'Start publishing or schedule a video post.' It distinguishes itself from taisly_posts_status by positioning that sibling as the follow-up check, but it does not explicitly contrast with taisly_reposts_create or other creation-adjacent 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?

It gives clear usage context: call only after explicit user confirmation, and after an immediate post use the returned historyId with taisly_posts_status. It does not state when-not to use this tool or explicitly route repost creation elsewhere, so it lacks full alternative-routing 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the agent knows it's a safe read operation. The description adds temporal context ('recent', 'history') but no further behavioral details like pagination or sorting. This adds some value beyond annotations but not extensive.

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 sentence that is concise and front-loaded, stating the action, resource, and purpose. 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?

The description covers the basic purpose but lacks details about return values (no output schema) or pagination behavior. Given the tool's simplicity and the supportive annotations, a score of 3 is reasonable.

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?

Input schema coverage is 100% with parameter descriptions for page, startTime, and endTime. The description does not add any extra meaning beyond the schema, so 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?

Description uses a specific verb ('List') and resource ('Taisly post history') and adds a usage context ('for status checks and audits'). It clearly differentiates from siblings like taisly_posts_create or taisly_posts_validate.

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 states when to use ('for status checks and audits'), providing clear context. However, it does not explicitly mention when not to use or list alternative tools among the siblings.

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 bar is lower; the description still adds real value by decoding the response path data.result[].status and explaining PENDING/SUCCESS/FAILED, which tells the agent the call is pollable and when the operation has reached a terminal 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?

Two tight sentences with zero filler; the identity of the call is front-loaded and the status-code decoding follows. 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?

With no output schema, the description usefully carries the return-value semantics, which is exactly what an agent needs for this read tool. It omits edge behavior (unknown id, partial platform failures, retry cadence), which keeps it just short of 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?

Schema description coverage is 100%, and the schema already documents both id and historyId including that historyId is an alias. The description repeats the historyId key but adds no format, example, or clarification of the id/historyId aliasing, so 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 (Fetch), resource (per-platform status for a Taisly post) and lookup key (historyId). It is readily separable from taisly_posts_list and taisly_posts_create because the resource is the status of one post rather than the post collection or a new 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?

Usage is only implied: the phrase 'by historyId' plus the schema note that historyId comes from taisly_posts_create signals this is a follow-up/polling call, but the description never states when to call it (e.g. after create, or to poll until terminal) or what alternatives exist. Adequate but leaves the agent to infer the workflow.

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 that this is a pre-publish check, which is useful workflow context, but says nothing about what a failed validation produces (errors, warnings, partial results) or whether it mutates any stored draft 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?

A single front-loaded sentence with the verb first and the validated surface enumerated. Nothing redundant and nothing padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter validation tool with nested settings objects and no output schema, the description omits the most decision-relevant behavior: what the caller gets back and what to do on failure. It is adequate to identify the tool but not to predict its response.

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 nested TikTok/YouTube settings are richly documented in-schema. The description only restates the top-level field names ('video path, platform IDs, caption, schedule') without adding format, ordering, or cross-field constraints beyond what the schema already says.

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 (validate) and enumerates exactly what is validated: local video path, destination platform IDs, caption, and optional schedule. The phrase 'before publishing' implicitly distinguishes it from taisly_posts_create, though the sibling is never named.

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?

'before publishing' implies the pre-flight use case, but the description never explicitly says to call this before taisly_posts_create, nor does it say whether validation is required or merely optional. The downstream alternative 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?

Annotations indicate readOnlyHint=false (write operation) and openWorldHint=true (potential side effects). The description adds context ('automation' and 'to one or more destination accounts') but does not clarify what the automation entails, when it triggers, or any required preconditions like connection status. It adds some value beyond annotations but lacks depth.

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 action ('Create a repost automation') and states the resource scope. No unnecessary words or redundant 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?

The description omits important details for a creation tool: it does not explain what happens after creation (e.g., whether it triggers immediately, expected response), does not reference sibling tools like taisly_reposts_list for follow-up, and does not mention any authentication or connection prerequisites. Given the absence of an output schema, the description should provide more guidance on the result or next steps.

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 parameters already documented ('Source platform ID' and 'Destination platform IDs.'). The description's mention of 'from one connected account to one or more destination accounts' aligns with but does not add new meaning beyond the schema. Baseline score 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 clearly states 'Create a repost automation' – a specific verb and resource (repost automation) – and distinguishes it from sibling tools like taisly_reposts_list (list reposts) and taisly_posts_create (create posts). It also defines the scope: 'from one connected account to one or more destination accounts.'

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 for creating repost automations but offers no explicit guidance on when to use this tool versus alternatives such as taisly_posts_create or taisly_reposts_list. No when-not-to-use or prerequisite information is provided.

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, destructiveHint=false, idempotentHint=true. The description adds 'configured repost automations' context but does not elaborate on behavior beyond what annotations cover. No contradictions.

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?

Single sentence, clear and direct. No unnecessary words. Front-loaded with the action and resource.

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 no parameters and no output schema, the description sufficiently explains what the tool returns (list of configured automations). Complete given the low complexity.

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?

No parameters exist, and schema coverage is 100%. Description mentions 'for connected social accounts,' implying auth context but no param details needed. Baseline 4 for 0 parameters 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?

Description clearly specifies the action 'List' and the resource 'configured repost automations for connected social accounts.' It distinguishes from sibling tools like taisly_reposts_create (create) and taisly_posts_list (list posts vs reposts).

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 explicit guidance on when to use this tool versus alternatives. While the context is simple and the tool is read-only, the description does not mention when not to use it or compare with siblings like taisly_reposts_create or taisly_posts_list.

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