qpost-mcp

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

With no annotations, the description carries the full behavioral burden, and it does add real context: the server is hosted and cannot read local files, so media must be a public URL or base64, and omitting scheduledFor publishes immediately. It says nothing about authentication, per-platform partial-failure behavior, rate limits, or whether a scheduled post can later be cancelled, which is a notable gap for a multi-platform write 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?

Two sentences, no filler, and the core action is front-loaded ahead of the operational constraints. Each clause (media sourcing, immediate-vs-schedule) carries distinct information.

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

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

For a 10-parameter mutation tool with no output schema and no annotations, the description covers the highest-risk ambiguity (media sourcing) and the scheduling switch, but leaves platform-specific metadata expectations, multi-platform failure semantics, and required-field behavior (caption/platforms/mediaKind) unaddressed. Adequate but with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 80%, so the baseline is 3, but the description adds a cross-parameter relationship the schema never states: media is supplied through either mediaUrl/imageUrls or mediaBase64, an either/or choice. The scheduledFor guidance duplicates the schema's own "omit to publish immediately" text, so the gain is real but partial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Create and publish (or schedule) a video or image post") plus the destination scope (connected platforms). It is trivially distinguishable from siblings like update_post, delete_post, and retry_post, since it is the only creation tool in the set.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit conditional guidance: "Omit scheduledFor to publish immediately" versus supplying it to schedule, and constrains the media source (public URL or base64). It does not name alternatives (e.g. use update_post to modify an existing post) or mention prerequisites such as connecting accounts, so it stops short of a full when/when-not treatment.

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 behavioral burden. It discloses two key traits: deletion is permanent and ownership is required. However, it does not mention potential consequences like cascading effects or error responses, which are relevant for a destructive tool. The core behaviors are covered, though not exhaustively.

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 with no wasted words. 'Permanently' and 'you own' are essential qualifiers that add value, and the structure is front-loaded with the action verb. It is a model of brevity.

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, no annotations—the description provides the essential action but leaves out important context such as the meaning of the 'id' parameter and success/failure behavior. It is minimally viable but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema defines only an 'id' parameter with no description, and the description does not mention it. Since schema coverage is 0%, the description should clarify that 'id' refers to the post being deleted, but it remains implicit. This creates a gap in parameter understanding.

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 tool's function: 'Permanently delete a post you own.' The verb 'delete' and resource 'post' make the action explicit, and the qualifier 'you own' distinguishes it from sibling tools like list_posts or update_post. This fully captures the tool's unique 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?

The description implies usage context—use when you own a post and want to permanently remove it—but does not explicitly mention alternatives or exclusions. There is no guidance such as 'use update_post to modify instead' or 'do not use for posts you don't own,' leaving the decision-making 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?

No annotations are provided, so the description carries the full behavioral burden, and it offers only a single clause. It discloses one useful trait (the response includes per-platform publish status), but says nothing about authentication/permission requirements, not-found or invalid-ID behavior, or how the per-platform data is shaped.

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 zero filler; every clause (single post, by ID, per-platform publish status) earns its place. It is efficient, though the extreme brevity is part of why other dimensions fall short.

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 single-parameter read tool with no output schema, the description is close to adequate: it names the resource, the lookup key, and one notable field in the response. However, with no annotations and no output schema, the absence of any error or permission context leaves a gap.

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 sole parameter `id` is undocumented in the schema and only obliquely covered by "by ID" in the description. No format, type expectation (UUID vs. numeric), or example is given, leaving the agent to guess at valid values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Get a single post by ID") and scopes it to exactly one item, which implicitly separates it from the sibling list_posts. It does not explicitly name any sibling (e.g., get_post_stats) for contrast, so it stops 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?

Usage is only implied: the agent must already hold a post ID, which is the natural trigger for this tool. There is no statement of when to prefer it over get_post_stats or list_posts, and no exclusions or prerequisites are given.

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

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

With no annotations provided, the description carries the full disclosure burden. It usefully discloses that data is 'read live from the platform (TikTok so far)' and includes each platform's public URL, which tells the agent about data freshness and platform coverage. However, it omits auth/permission requirements, latency or rate-limit expectations, and behavior when a platform is unsupported.

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 naming the returned fields and the data source; there is no redundant filler. It is slightly dense but every clause (metrics, per-platform, live, URL) adds 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?

With no output schema or annotations, the description does well to enumerate the returned metrics and mention the public URL, but it leaves gaps: the meaning of the required 'id' parameter, error/edge cases for unsupported platforms, and freshness caveats beyond 'live'. Adequate but incomplete for a tool with zero structured documentation.

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% for the single 'id' parameter, so the description must compensate, yet it never explains that 'id' identifies the post whose stats are fetched. The agent must infer the parameter's meaning from the tool name alone.

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 conveys that this retrieves engagement metrics (views, likes, comments, shares) for a published post, which distinguishes it from the sibling get_post (which returns the post itself) and the mutation tools. It lacks an explicit verb+resource framing like 'Retrieve statistics for a post', but the intent is unambiguous.

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 explicit when-to-use guidance, no mention of alternatives such as get_post, and no stated prerequisites (e.g., the post must be published). Usage is only implied by 'How a published post is doing', leaving the agent to infer when this tool is appropriate.

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 burden, and it does signal this is a non-destructive listing tied to posting eligibility. However, it says nothing about authorization prerequisites (must an account already be OAuth-connected), rate limits, or what happens when zero accounts are connected.

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 short sentences with zero filler, and the 'what' precedes the 'when to call' guidance. Every clause earns its place.

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

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

For a zero-parameter read tool with no output schema or annotations, the description conveys what is returned and when to invoke it. It leaves minor gaps around the shape of the returned accounts and behavior on an empty result set, but nothing an agent needs to call it correctly 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?

The tool takes no parameters, so there is no parameter semantics to explain and the baseline is 4. The description correctly implies an unfiltered listing of all connected accounts.

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 (List) and resource (YouTube/TikTok/Instagram accounts connected to the QPost account), and the platform enumeration makes its scope concrete. It is trivially distinguishable from the post-mutation siblings like create_post or delete_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?

Explicitly instructs the agent to call this before creating a post to learn which platforms are available, which names the relevant sibling (create_post) and the triggering condition. It stops short of stating when-not to call it or naming other alternatives, so it is clear context rather than a full routing rule.

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

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

No annotations are provided, so the description carries the full behavioral burden. "List" implies a read operation, but it says nothing about authentication, pagination, result limits, or ordering. For a list endpoint with zero annotation coverage, this is a significant transparency gap.

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 primary action and its optional filters are stated immediately.

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

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

For a two-parameter list tool, the description is minimally sufficient: it identifies the resource and both filters. It omits pagination behavior and does not compensate for the absence of an output schema, leaving some operational details unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the schema itself provides enums for both parameters, and the description adds that status and platform are optional filters. That confirms their role beyond the raw schema, though it offers no additional syntax or default behavior. A baseline 3 is appropriate because the enums do much of the documentation work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource ("List posts") and scopes it to "this account," which clearly separates it from get_post, create_post, and update_post. It does not explicitly name a sibling alternative, but the list operation is unambiguous against the surrounding tools.

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 states that filtering by status or platform is optional, which implies straightforward usage. However, it gives no guidance on when to prefer this over get_post or get_post_stats, nor any exclusions or prerequisites. Usage is implied but not elaborated.

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 full burden for side effects. It only says 'retry' without disclosing what that entails (e.g., whether it creates a new publishing attempt, updates status, or is idempotent). This leaves the agent uncertain about consequences.

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 one-sentence description is concise and front-loaded, with 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?

Although the tool is simple with one parameter and no output schema, the lack of behavioral details and the vague parameter meaning mean the description is not fully complete for an agent to safely invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has a single 'id' parameter with no documentation. The description implies 'id' refers to the post that previously failed, adding some meaning, but it does not clarify if this is the post ID or an attempt ID, nor does it provide examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action (retry) applied to a specific resource (publishing a post) with a precondition (previously failed). This distinguishes it from sibling tools like create_post or update_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?

The phrase 'previously failed' gives a clear condition for when to use the tool. However, it does not explicitly name alternatives or state when not to use it, so it lacks 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?

No annotations are provided, so the description carries the full burden. It does disclose one meaningful behavioral trait — patch semantics, 'Only the fields you pass are changed' — which is not derivable from the schema. It omits permissions, reversibility of status transitions, and whether SCHEDULED requires a scheduledFor value, so it is only partially transparent for a mutation 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?

Two short sentences, zero waste, and the patch-semantics caveat is front-loaded right after the field list. Nothing could be cut without losing information.

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

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

For a 5-parameter mutation tool with no annotations, no output schema, and no schema descriptions, the definition is thin. The schema's enums and date-time pattern partially self-document the fields, but the description does not cover required-ness, status transition rules, or the scheduledFor/status dependency an agent must reason about before calling it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 5 parameters, so the description must compensate. It names four of the five fields (caption, schedule, timezone, status), which maps loosely onto scheduledFor/status/caption/timezone, but adds no enum meaning, no ISO-8601 format hint for the scheduled field, no note that id is required, and no explanation of the null case.

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?

Specific verb (Update) plus resource (a post) and an enumeration of the mutable fields (caption, schedule, timezone, status). It is easily distinguished from create_post/delete_post/get_post by name and description, though it never explicitly contrasts itself with retry_post, the one sibling whose purpose overlaps on 'status changes'.

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 second sentence implies the intended usage pattern (partial/patch edit rather than full replacement), which is genuinely useful. However there is no explicit when-to-use vs. when-not guidance: nothing says to prefer retry_post for FAILED posts, whether editing a POSTED post is allowed, or what prerequisites (auth, ownership) apply.

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