Vokolla Press Release Agent

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

Goes well beyond the annotations by disclosing that it 'Uses the AI quota and sends content to the AI provider' (external transmission plus cost) and that the result is a 'proposal, not an approved placement or submission.' The annotations only flag openWorldHint and non-idempotence; the description adds the quota/transmission and non-committal-result 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 tight sentences, purpose front-loaded, no filler. The caveat about quota and proposal status is placed after the core purpose, which is the right ordering.

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 non-idempotent, open-world AI tool with a large nested input and no output schema, the description covers the workflow stance and side effects but leaves the input structure and the shape of the returned proposal entirely unexplained. 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?

The description mentions no parameters at all, and schema description coverage is effectively 0% across the large nested content object (only 'body' carries any description). With ~20 undocumented nested fields, the description should compensate for the coverage gap but does nothing here.

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: 'Prepare a factual revision against USA Today editorial formatting requirements.' This is distinct enough from siblings like ai_draft_release and ai_review_release to be selectable, though it never names or contrasts those alternatives explicitly.

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

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

Usage is implied rather than stated. The line 'Returns a proposal, not an approved placement or submission' situates it in the workflow but does not say when to choose it over ai_draft_release or ai_review_release, nor what prerequisites must be met first.

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 it is a non-read-only, open-world, non-idempotent call, and the description adds real behavioral context beyond that: materials are sent to a third-party AI provider, the account's MCP AI quota is consumed, and nothing is persisted or published. It stops short of describing failure modes or latency, but the privacy/cost/side-effect boundary is well disclosed.

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 tight sentences with the core action front-loaded and no filler beyond the mildly redundant 'Use Vokolla AI' opener. The quota and no-save constraints are placed where an agent will read them before invoking.

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 non-idempotent AI-generation call with no output schema, the description covers data egress, quota cost, and non-persistence reasonably well, and 'Missing facts are marked for the customer' hints at the returned draft's shape. It is thin on the four parameters and on what the caller actually receives back.

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 carries the full burden, yet it only loosely maps to 'materials' via 'notes or extracted document text'. The plan, language, and releaseLanguage parameters, the 20k material cap, and the fact that materials is the sole required field are all left unexplained.

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 (draft) plus resource (press release) and names the input source (customer-supplied notes or extracted document text). It is distinguishable from siblings like ai_review_release and ai_adapt_release, though it never explicitly says how it differs from them.

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 input-shape guidance (notes or extracted text) and implies a follow-up step by stating it 'Does not save or publish', which points toward save_draft. However it never states when to prefer this over ai_adapt_release or ai_review_release, nor any prerequisites.

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

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false), the description discloses three useful traits: content is transmitted to an external AI provider, the call consumes the MCP AI quota, and the saved draft is not modified. That is real operational context an agent needs before invoking. It stops short of noting whether results are cached or how quota exhaustion manifests.

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 short sentences, each carrying distinct information (what it returns, what it does externally, what it does not change), with the core purpose front-loaded. Nothing is padded or repeated.

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 should characterize the return value; it only gestures at 'editorial issues and suggested replacements' without describing shape, granularity, or how to apply the replacements. It also omits that the required content.body is the review target, leaving the agent to reverse-engineer the nested payload.

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

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

Schema description coverage is 0% and the nested content object carries roughly twenty undocumented fields, including the required body. The description only implies that the 'manuscript' is the payload; it explains nothing about plan, language, or which content fields drive the review, so it fails to compensate for the coverage gap.

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: it finds editorial issues and suggested replacements in a press release manuscript using the same AI review as Vokolla. That is concrete enough to distinguish it from a status or listing tool, but it never names or contrasts with the closest siblings (check_release, get_editorial_guidelines), so the agent must infer the boundary.

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

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

Usage is implied rather than stated: 'Does not modify the saved draft' and the quota note suggest this is a non-persisting pre-publish review step. There is no explicit when-to-use or when-not-to-use guidance and no pointer to check_release or get_editorial_guidelines as alternatives for lighter validation.

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 readOnly/non-destructive/idempotent/closed-world, and the description adds meaningful context beyond them: it performs no AI call, publishes nothing, and sanitizes HTML by removing active content. That sanitization/transformation behavior is a real disclosure. It stops short of describing how check failures are reported, so not a 5.

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 short front-loaded sentences, purpose first, with zero filler. Every sentence carries distinct information (what, no-AI/no-publish, sanitization).

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 validation tool with a complex nested schema, no output schema, and 0% parameter coverage, the description omits what a failing check returns and how results are surfaced. The core 'what it does' is complete, but an agent lacks the surrounding detail needed to interpret outcomes.

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

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

Schema description coverage is 0%, and with 3 parameters including a nested 20-field content object, the description must compensate but does not. It gives only a faint clue that 'body' holds HTML ('active content is removed') and never explains the plan or language enums or the content fields.

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 action (deterministic word/link/contact checks) on a specific resource (a manuscript), and explicitly distinguishes itself from the AI siblings via 'No AI provider call or publication.' An agent can tell it apart from ai_review_release/ai_adapt_release without opening either schema.

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

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

The 'No AI provider call' phrasing implicitly positions this as the non-AI validation alternative to the ai_* siblings, but it never states when to prefer it, ordering relative to ai_review_release, or prerequisites. Usage must be inferred.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only that the payload is editorial rules plus supported categories; with no output schema, it does not say how the optional plan changes the result or what shape the data takes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. It is efficient, though its terseness borders on under-specification rather than genuine 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 two-parameter tool with no output schema and no schema descriptions, the definition is too thin: it does not clarify what is returned, how the selected plan shapes the rules, or how language affects output. Annotations cover the read-only safety profile, but the informational contract 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 0%, so the description carries the full burden, yet it never explains the 'plan' enum (brand-starter, global-reach, etc.), its null default, or the 'language' enum. 'For a distribution package' is the only hint, and it does not map cleanly onto a parameter named 'plan'.

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: retrieves Vokolla editorial rules and supported categories, scoped to a distribution plan. That is far more informative than the title, though it does not explicitly differentiate itself from the release-oriented siblings (ai_draft_release, check_release, etc.).

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

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives or exclusions. The phrase 'for a distribution package' faintly implies a pre-distribution step, but the agent is left to infer the trigger entirely.

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 readOnly, idempotent, open-world, non-destructive, so the safety bar is low. The description still adds real context beyond them: 'synchronized' signals the data is a periodically refreshed snapshot, 'Coverage URLs are third-party data' warns about external provenance, and the explicit exclusion of submit/retry/cancel clarifies the boundary with action tools.

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 short sentences, each doing distinct work: the operation, the data-provenance caveat, the negative capability statement. No filler, no restatement of the title, and the core purpose is front-loaded.

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 should indicate what 'status' and 'coverage' actually return, but it stays abstract. It does cover freshness semantics, access scope, provenance and non-mutation, which is enough to call the tool safely, but an agent cannot anticipate the result shape or possible status values.

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?

One required parameter with 0% schema description coverage, so the description must carry meaning for releaseId. It only states the ownership constraint ('a release owned by this account'), which is useful access-scoping, but adds nothing about the identifier's origin or how to obtain it. The schema itself supplies the UUID format and validation pattern, keeping this at 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?

States a specific verb ('Read') and resource ('latest synchronized status and coverage') scoped to 'a release owned by this account'. That ownership qualifier meaningfully narrows the tool relative to list_releases or ai_review_release. However, it never names or distinguishes itself from the closest sibling, check_release, so the agent must infer the difference.

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

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

Usage is implied rather than stated: 'Does not submit, retry or cancel anything' rules out the mutation-oriented siblings, and 'owned by this account' scopes the query. There is no explicit 'use this when / use X instead' sentence, so an agent comparing against check_release gets no 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, idempotentHint, non-destructive, and closed-world, so the safety profile is fully covered by structured data. The description adds one meaningful behavioral fact beyond annotations – that no order is created and checkout confirms final price – which is genuinely useful. It doesn't cover locale behavior or whether prices are region-specific. Adds some value, so a 3.

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, front-loaded with the resource and scope, then the behavioral caveat. Efficient, though the first sentence is a fragment rather than a clear action statement.

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 single-parameter read-only listing tool with no output schema, the description covers the essential scope and the no-order caveat. But it omits what the returned packages contain and what the language parameter does, leaving the agent to infer localization behavior. 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 0% and the single 'language' parameter (enum en/zh-Hans, default en) is undocumented in prose. The description says 'in USD' but never explains that the language parameter controls localization of the returned package list. With zero schema coverage, the description should compensate for this gap and does not.

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 title and description indicate this returns retail package/pricing options for Vokolla, so the resource is identifiable. However, the verb is weak – 'Current public retail packages' is a noun phrase, not a clear action, and the description doesn't explicitly say it lists or compares packages. It's distinct from the release-related siblings, but the purpose could be sharper.

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 sentence 'No order is created; checkout confirms the final price' implicitly tells the agent this is a pre-purchase/browse tool rather than a purchase tool, which is useful context. But it doesn't state when to use this vs. alternatives, and there are no sibling tools covering package browsing, so there's little alternative routing needed. Implied usage only.

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 readOnly/idempotent/non-destructive, so the bar is lower, and the description still adds real context: no new status check is triggered and billing/contact fields are excluded from results. It stops short of disclosing pagination or result-size behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, zero filler, with the core read behavior and the key exclusions front-loaded. Every clause carries 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 and no parameter documentation, the description covers the return content at a high level ('saved status information') but leaves pagination semantics and the exact shape of returned records unspecified. Adequate for a simple list, but not 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 0% for the two pagination parameters, so the description carries the burden of explaining them and it says nothing about limit or offset. 'Most recent first' hints at ordering but not at paging, capping, or defaults.

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 ('Read ... release records') plus scope ('this account's') and ordering ('most recent first'). It implicitly separates itself from status-checking siblings ('without triggering a new status check'), but never names an alternative tool outright.

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 context for when this is the right call: you want stored/synchronized status data rather than a live check. That contrast with check_release/get_release_status is useful, though it is expressed negatively rather than as an explicit 'use X when Y' rule, and no prerequisites are stated.

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=false, idempotentHint=true and destructiveHint=false, so the bar is lower; the description still adds real value by ruling out mutation of existing drafts and order placement, and by clarifying that review/payment stay outside the tool. It omits auth/permission requirements, but the boundary statements go beyond the structured hints.

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?

Four short sentences, all front-loaded, with the core action first and boundary constraints after. No filler and every sentence carries a distinct constraint.

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 and a large undocumented nested content schema, the description is adequate but not sufficient: an agent still lacks guidance on the plan enum, scheduling fields, and what a returned draft identity looks like. The negative scoping (no order, no mutation) is a good compensating detail.

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 effectively 0% across a 23-field nested content object, so the description carries a heavy compensation burden. It does explain the requestId idempotency semantics (same UUID on retry, new one for new content), which is genuine added meaning, but says nothing about plan, scheduleMode, scheduledAt, categories or the other content fields.

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 ('Create an account-owned draft') and sharpens scope with negatives ('Never changes an existing draft or places an order'). It does not, however, distinguish itself from the very similar sibling ai_draft_release, so an agent gets no help choosing between them.

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 a clear use precondition ('Requires an explicit request to save') and gives retry guidance ('Reuse the same UUID requestId on retry; use a new one for different content'). It names no alternative tools, so there is no explicit when-not or sibling routing despite the presence of ai_draft_release.

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