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

With no annotations, the description carries the full burden and delivers: it warns this publishes a real listing, discloses the Pro-plan requirement and the resulting 403 'plan limit' error, and explains the return contract for every `state` value (listed/pending/failed) including that `failed` refreshes the draft and that `pending` must not be resent.

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?

Purpose is front-loaded in the first clause and every sentence carries operational content. It is dense rather than padded, though the long single paragraph packs several distinct concerns (precondition, sourcing, confirmation, plan gating, return states) that could be marginally tighter.

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

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

No output schema exists, but the description compensates by fully enumerating the `state` outcomes and the `message`/`draft` fields carried on failure. For a nested-object, plan-gated mutation tool, 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?

Schema coverage is 100%, so the `edits` semantics are already documented. The description still adds value by framing `edits` as optional correction and telling the agent where new values should come from (measured size, actual brand), which is guidance the schema does not provide.

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+resource ('Approve a review draft and send it to the marketplace') with an explicit secondary capability ('optionally correcting fields first'). It also distinguishes itself from the sibling list_drafts, which is framed as the read step that precedes it.

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

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

Gives explicit when-to-use ('the way to resolve a `failed` draft'), a required precondition (read the draft with list_drafts first), a data-sourcing rule (take the value from the product's own details), and a gating action (confirm with the user before sending). It also names a when-not-to-act case: re-sending on a `pending` result.

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 present, so the description carries the full burden. It discloses that Intesa runs inside the seller's account, takes up to a minute due to a multi-step tool loop, and can perform bulk jobs, search history, and read support docs. This provides useful context about latency and scope, though it does not explicitly warn about potential side effects of bulk actions.

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 four sentences, each earning its place: defining the assistant, listing capabilities, contrasting with direct tools, and setting latency expectations. It is front-loaded with the name and purpose, and contains no filler.

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

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

Given the complexity of this open-ended assistant tool and the absence of an output schema, the description covers the key aspects: capabilities, use case, latency, and relationship to sibling tools. It hints at return values by mentioning the conversation_id, but does not detail the reply format, which would be difficult for such a flexible tool. Overall, it is sufficiently complete for practical 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 100%, with both message and conversation_id fully documented in the schema. The description adds no additional parameter-level detail; the only extra is the mention that conversation_id allows threading, but this is already in the schema description. 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 identifies the tool as an assistant to be asked questions, using the verb 'Ask' with the resource 'Intesa'. It distinguishes from siblings by explicitly stating it can do things the MCP server cannot, such as diagnosing sync issues and explaining listing errors, making its purpose specific and differentiated.

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 to prefer direct tools like list_products, crosslist, and get_orders for simple reads and writes, and to use this tool for diagnostic or open-ended questions. It even provides an example ('why did my last five Vinted listings fail?'), giving clear when-to-use and 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?

No annotations provided, so description carries full burden. Discloses asynchronous behavior, queued status, and dedup logic. Adds valuable context beyond basic listing.

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?

Description is front-loaded with purpose and follows with caveats. Each sentence adds value, though slightly verbose with repetition of honesty instruction. Efficient overall.

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

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

No output schema, but description mentions reading 'status' per channel. However, lacks full response structure details. Adequate for a 2-param list tool but could be more 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 coverage is 100%, so baseline is 3. Description does not add additional parameter semantics beyond schema; schema already describes vids and targets clearly.

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 'List existing FLUF products on one or more marketplaces' with specific verb and resource. It distinguishes from sibling tools like list_products and list_channels by focusing on cross-listing to marketplaces.

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?

Describes when to use (list products on marketplaces) and provides important caveats (async behavior, queued status, 30-second dedup). Lacks explicit alternatives or when-not-to-use, but 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?

With no annotations, the description carries the full burden and does so thoroughly: it explains the default (record-only removal, listings untouched), the destructive opt-in (also_delist ends live listings, irreversible), recoverability (Recently Deleted, 60-day restore), and the auth/plan prerequisite (Pro plan, 403 'plan limit' on read-only tokens). This is exactly the behavioral context an agent needs before a destructive call.

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?

Front-loads the action, then the default behavior, then the destructive opt-in, then recovery and prerequisites. Every sentence carries distinct information with no filler.

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

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

A destructive tool with no annotations and no output schema, yet the description covers default vs opt-in behavior, irreversibility, recovery window, and plan gating. Nothing an agent needs to call this safely 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 description coverage is 100%, so both parameters are already documented in the schema, including the default false and the irreversibility of also_delist. The description reinforces but does not extend that meaning, so the baseline 3 applies.

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

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

Opens with a specific verb+resource ('Delete FLUF products') and immediately scopes it. No sibling tool performs deletion, so there is no ambiguity to resolve; the agent knows exactly what this does from the first sentence.

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

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

Gives clear usage context ('Suited to sold-out or obsolete inventory') and a mandatory workflow step ('Always confirm with the user first and list which products will be deleted'). No sibling alternative exists to route to, so no exclusions are needed, but the when-to-use guidance is concrete and actionable.

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 must carry the full burden. It mentions a 'unified shape' but lacks details on pagination, data freshness, authentication, or rate limits. Minimal behavioral context beyond the schema.

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 clear sentence (15 words), front-loading the purpose. Every word is necessary and there is no 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?

With 7 optional parameters and no output schema, the description is too brief. It does not explain what 'unified shape' means, pagination behavior, or how filters interact. The agent lacks sufficient context for correct invocation.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; it does not elaborate on parameters or their usage.

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 'Get the seller's orders across every connected marketplace, in one unified shape,' specifying the verb and resource. It distinguishes from siblings like list_products (products vs. orders) and list_channels (channels vs. orders).

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 retrieving orders from all marketplaces but does not explicitly state when to use it versus siblings or when not to use it, missing alternatives or exclusions.

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

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

No annotations provided, but the description discloses that the roster differs per account and changes over time, offering useful behavioral context. However, it does not mention any permissions or potential side effects, which is acceptable for a read-only listing 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, front-loaded with the main action, no wasted words. Perfectly concise and well-structured.

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?

While there is no output schema, the description hints at the return format by mentioning connected vs. listable channels. For a simple listing with no parameters, this is sufficiently 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?

There are no parameters (empty schema), so the description does not need to add parameter meaning. A baseline of 4 is appropriate given the absence of parameters.

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

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

The description clearly states the tool lists marketplace channels available on the account, distinguishing between connected and listable. It contrasts with siblings like 'crosslist' which posts to channels, and 'list_products' which lists products.

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 advises calling this before 'crosslist' instead of guessing channel names, noting that the roster varies per account and over time. This provides clear when-to-use and when-not-to 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 and does well: it explains that `failed` means a marketplace refused for a fixable reason, that `reason` holds the objection and `fields` carries editable values, that `pending_review` is merely awaiting go-ahead, and that drafts disappear from the list once the item goes live. It stops short of stating pagination behavior or any permission/auth requirements.

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?

Front-loaded with the core purpose, then layers state semantics and the next action in four tight sentences. Dense but every clause carries information; no filler or repetition of the tool name.

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

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

There is no output schema, so the description usefully documents the meaningful return shape (reason, fields, editable flags, select options) as well as the lifecycle behavior. Missing only minor items such as pagination echo or sorting, which is acceptable for a filtered-list 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?

Schema description coverage is 100%, so every parameter is already documented in the schema, including the status enum meanings and by_channel note. The description adds workflow meaning around statuses but no syntax or format detail beyond what the schema supplies, so baseline 3 applies.

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

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

Opens with a specific verb+resource ('List the seller's review drafts') and immediately scopes it as 'listings FLUF has prepared but not sent', which separates it from sibling list_products and from approve_draft. The definition of each draft state makes the object of the tool 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?

Explicitly routes the agent onward: read the draft, derive the corrected value from the product itself ('never invent one'), then call approve_draft with the edits. That is clear when-to-use context and names the next tool. It does not, however, contrast with alternatives like list_products or discuss when not to call it.

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

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

With no annotations, the description carries the full burden and delivers: `status` is a stale channel record, not a live check; `total` counts everything the filter did not exclude; relists mint new listing ids so two 'active' rows are usually not duplicates. It also surfaces the downstream risk (never advise ending a listing from this tool alone).

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?

Purpose is front-loaded and the caveats are dense but each earns its place (staleness, counting, duplicates, safety). It is longer than typical and the bolded middle block leans heavy, but no sentence is 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?

There is no output schema, and the description compensates by naming the fields returned (vid, liveness, last_seen_at, last_seen_age_hours) and their semantics. For an 8-param read tool with no annotations, 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?

Schema coverage is 100%, so the baseline is 3, but the description adds cross-parameter semantics the schema alone leaves implicit: that `liveness` narrows `total` while `status` does not, and that omitting status yields in-stock plus, via search, sold items. That interplay is genuinely useful beyond the per-field text.

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 ('List the authenticated seller's FLUF products') plus scope, and immediately enumerates the row payload (vid, title, price, stock, source channel, live channels). This clearly separates it from siblings like list_drafts and list_channels.

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 tells the agent when to use `liveness: "confirmed"` (counting a live catalogue, judging duplicates), warns against filtering rows manually and quoting `total`, and states the tool must not be used alone to justify ending a listing. Alternatives and exclusions are all named.

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

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

With no annotations, the description carries the full burden and does so: it discloses the delivery destination (a human inbox as a direct message), the reply channel (the user's FLUF inbox), that account identity is auto-attached, and that retrying quietly instead of filing is wrong. These are non-obvious operational facts an agent could not infer from the schema.

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?

Front-loaded with purpose, then conditions, then constraints; every sentence contributes something (trigger conditions, exclusions, length, identity handling, reply path). It runs somewhat long for a four-parameter tool, but the density is justified rather than 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?

No output schema and no annotations, yet the description covers what the agent needs: when to file, when not to, how long the report should be, what the fields should contain in spirit, that identity is auto-attached, and where the reply lands. Nothing material 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 baseline is 3. The description adds real meaning beyond the schema: the 'keep it short' constraint, the rationale (long reports get read last), and the explicit prohibition on asking for identity or including background/retried steps. It stops short of documenting each field individually, which the schema already handles.

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?

Opens with a specific verb and resource: 'Raise a bug with FLUF support.' The two enumerated triggering situations make the scope unambiguous, and no sibling tool (list_products, crosslist, approve_draft, etc.) overlaps with this 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?

Explicitly names both when-to-use conditions, including the counterintuitive one (agent hit the problem itself), and adds a clear when-NOT-to-use exclusion list (expired token, lapsed plan, channel reauthorisation) with the alternative action ('tell them the fix instead').

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