autowhisper-mcp

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

With no annotations, the description carries the full burden and delivers: approve_feed_item schedules to every platform, starts a render and charges credits, schedules nothing when no platform is connected, and connecting later does not retroactively publish. regenerate_content rewrites in place (same record id) and always returns a confirmation because it spends credits. These are exactly the side effects, costs and irreversibility cues 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?

Dense but front-loaded: it leads with the tool's purpose, then the confirmation requirement, then the two riskiest actions. Every sentence adds operational meaning, though the block is long and the per-action clauses could be tightened.

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 9 enum actions, no annotations and no output schema, the description richly covers approve_feed_item and regenerate_content but leaves reject/dismiss/publish_content/reschedule_post/retry_post/mark_as_published/boost_post nearly unaddressed. Adequate for the riskiest paths, incomplete for the rest.

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 89%, so the schema already documents the parameters, setting the baseline at 3. The description adds only marginal meaning (regenerate_content takes content_type + content_id rather than feed_item_id), which is useful but largely restates the same distinction the schema descriptions already make.

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 and scope: 'Run an explicit feed or post action without an AI chat turn.' It also distinguishes itself from the AI-chat path and from the confirmation sibling, so an agent can tell what this tool is for without opening the 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?

Clearly routes the agent: high-impact actions return a message_id that must be confirmed via autowhisper_confirm, and it explains the approve_feed_item spend semantics. It does not contrast with other action-adjacent siblings such as autowhisper_edit_content, so usage guidance is strong but not exhaustive.

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 unusually well: it discloses that posting does not equal traffic, that reach comes from the user's paid ads, that product creation requires a URL because the image is scraped from the page, and that text-only descriptions and placeholder/stock images are rejected. It still omits the side-effect profile an agent needs — whether content is published immediately or gated behind autowhisper_confirm, and whether this operation draws on autowhisper_wallet funds.

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 action, then capability buckets, examples, and scope caveats. Every sentence is doing work — the examples disambiguate the natural-language parameter and the 'honest scope' note prevents a misuse class — though the three-quote example block is on the verbose side for a single-paragraph tool.

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 only promises 'its reply,' never characterizing the response or whether the call is synchronous. For a tool that generates creatives and posts across 30+ networks, the omission of the publish/confirm flow and any cost or rate-limit context leaves a meaningful gap despite the otherwise thorough scope notes.

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 the workspace_id language-inheritance and token precedence rules are already fully documented in the schema (baseline 3). The description nonetheless adds real semantic value by constraining how instruction and product_id must be constructed: a product only gets created if a URL is supplied, since the CMO extracts the image from the page.

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 — send a natural-language instruction to an AI CMO and get its reply — and enumerates three concrete capability areas (creative generation, funding/targeting advice, channel maintenance). An agent can tell what this does, but nothing in the text distinguishes it from the closely-named sibling autowhisper_action, so sibling differentiation is absent.

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 'Best at' buckets plus three worked example instructions give clear positive guidance on when to reach for this tool over a structured endpoint. However, no exclusions or alternatives are named (e.g., when to use autowhisper_action or autowhisper_products instead), so the routing guidance is context-rich but one-sided.

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

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

With no annotations, the description carries the burden, and it does convey that this gates a 'high-impact action' and that the decision is binary. However, it omits what happens to the action on 'no', whether a pending confirmation expires, and what permissions are needed to approve. Useful context, but not the full behavioral picture for an approval-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 tight sentences with the action and its trigger front-loaded, then the invocation mechanics. Nothing extraneous and nothing buried.

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?

Covers the essential flow an agent needs for a confirmation tool with no output schema, and the schema fully fills in the workspace/token details the description skips. Only edge-case behavior (what declining does, confirmation lifetime) is left implicit.

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 message_id, the yes/no enum, workspace_id, and token precedence. The description only restates that message_id comes from the confirmation request and that decision is 'yes' or 'no', adding little beyond the schema's own text. 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?

Names a specific verb pair (approve/decline) and the exact resource (a confirmation request) it acts on. It also identifies the originating siblings (autowhisper_cmo, autowhisper_action), so an agent can distinguish this from the tools that raise the request.

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?

States the selecting condition clearly: use this when the CMO or autowhisper_action asked you to confirm a high-impact action, passing the message_id it supplied. There are no explicit exclusions or named alternatives, but the trigger is unambiguous enough to route correctly.

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

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

With no annotations, the description carries the full burden. It usefully discloses two behaviors: no credit spend (cost transparency) and full replacement semantics for body. However, it does not clarify whether omitted fields are left untouched or cleared, nor any permission/auth requirements, leaving notable mutation behavior undisclosed.

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 sentence, followed by the body semantics and the ID disambiguation. It is efficient overall though the ID explanation is dense and slightly crowded.

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 40% schema coverage and no annotations or output schema, the description is adequate but incomplete: it never explains partial-update behavior for the many optional field parameters, which is important 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 coverage is only 40%, so the description must compensate. It adds meaning for body ('full replacement copy/story') and reiterates the content_id resolution detail already present in the schema, but leaves cta, hook, tone, title, and keywords completely undocumented in both places.

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 clear verb+resource ('update exact content fields') and adds a meaningful scope contrast: this is a direct edit that avoids a generation run or credit spend. It does not name a specific sibling tool, so the differentiation from generation-based siblings is implied rather than explicit.

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?

Guidance is present: use this for direct field edits instead of a generation run, and pass body for a full replacement. This gives usable when-to-use context, but no explicit when-not-to-use or named alternative tool 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?

No annotations are provided, so the description carries the full burden. It usefully discloses the return shape (status counts, per-row actions with arguments, both the review-card id and content id), but says nothing about permissions, read-only vs mutating nature, rate limits, or pagination 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 dense sentences, front-loaded with the tool's output purpose followed by the id-routing detail. Little waste, though the backtick formatting is slightly heavy; nothing is redundant.

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 must explain the return shape, and it does: it describes status counts, available actions with arguments, and the two id formats. It leaves out filtering/pagination behavior and permission requirements, but the core calling information is present.

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 all three parameters (status enum, workspace_id, token) are already fully documented in the schema, including the default-current-workspace and token-precedence semantics. The description adds no parameter-level detail beyond that, 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?

States a concrete resource and scope ('CMO feed list with status counts and actions available on each row'), and differentiates itself from siblings by naming exactly which tool each printed id routes to (autowhisper_action vs autowhisper_edit_content). The verb is implied rather than stated ('list'), which keeps it just 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 implied rather than stated: an agent can infer it should call this to discover feed rows and the ids needed for autowhisper_action/autowhisper_edit_content. There is no explicit when-to-use or when-not-to-use guidance, and no mention of alternatives (e.g. autowhisper_status for workspace ids).

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, and it does real work: it declares read-only behavior, the single-workspace scope, and the important null-vs-0 semantic for ad_spend_cents ('null means we cannot answer, 0 would assert nothing was spent'). It stops short of describing pagination, latency, or auth requirements beyond the token param, so it is strong but not exhaustive.

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 usage, then the null-vs-0 caveat that materially changes interpretation. The three sentences are dense but each earns its place; only the null caveat sentence runs slightly long.

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 read-only analytics tool with no output schema, the description covers intent, scope, returned data shape, and the one ambiguous output value (ad_spend_cents null vs 0). An agent has everything needed to call it and interpret the result correctly.

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 the schema already documents window_days, workspace_id, and autowhisper_token, including the omission-defaults-to-current-workspace rule. The description adds no parameter-level syntax or format detail beyond the 'ONE workspace' scoping emphasis, 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?

States a specific verb and resource — read-only cross-channel performance for ONE workspace — and enumerates the returned structures (four-layer funnel, per-channel breakdown, ad spend). It explicitly distinguishes itself from autowhisper_feed and autowhisper_posts, which 'only say what was made and sent, never whether it worked.'

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 ('answer how published content is actually doing, and before advising which creative to fund or scale') and names the sibling tools it supersedes for that question. Nothing about tool selection 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?

No annotations are provided, so the description carries the full burden. 'List' implies a read, and 'Fast' hints at a cheap/cached call, but it never states that the operation is non-mutating, whether it requires auth, any rate limits, or what the health field contains.

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 short, front-loaded sentence with no preamble or repetition — nothing is wasted. It is arguably too terse, and 'Fast' is mildly promotional rather than informative, keeping it below a 5.

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-required-param read tool with fully documented parameters, the description is adequate but thin. With no annotations and no output schema, it should at least sketch the shape of a 'platform' entry and its health value, which it does not.

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 workspace_id and autowhisper_token are already documented, including the current-workspace default and token precedence. The description only reinforces the single-workspace scope and adds no syntax or format detail beyond the schema, 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?

States a specific resource (connected platforms) and two things it reports: the list itself and connection health, scoped to ONE workspace. It is distinguishable from siblings like autowhisper_status or autowhisper_wallet, though it never names an alternative to disambiguate.

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

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

The description gives no when-to-use guidance, no exclusions, and does not point to a sibling for related data. The only routing hint (use autowhisper_status for other workspace ids) lives in the schema, not the description.

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 supplied, so the description carries the full disclosure burden. It adds genuinely useful content by explaining that failed rows carry a reason and a retry signal, and that 'needs reconnect' requires a human to re-authorise the channel. However, it does not state that the operation is read-only, whether results are paginated or ordered, or any auth/rate constraints.

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, both front-loaded and non-redundant: the first states what the tool returns, the second explains failure-row semantics. No filler 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?

With no output schema and no annotations, the description does some of the work by explaining the meaning of failed rows and the retry signal. It still omits what a normal row contains, pagination/limit behavior, default status scope, and ordering, which an agent needs to consume the output correctly.

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 the schema already documents status, workspace_id (including the current-workspace default and the pointer to autowhisper_status), and autowhisper_token. The description mentions status filtering but adds no value or enum values beyond that, 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?

The description states a specific verb and resource ('post queue list') and its scope ('optionally filtered by status'), which is enough to distinguish it from the sibling action/status/wallet tools by domain. It never names an adjacent list-style sibling, so differentiation is implied rather than explicit.

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 only usage signal is 'optionally filtered by status', which implies a read of the queue but gives no when-to-use/when-not and names no alternative (e.g. versus autowhisper_action or autowhisper_feed). The failure-row explanation hints at diagnostics use, but that is inference, not 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; it usefully discloses the shape of each returned row (id, type, main-image flag, storefront link), which substitutes for the missing output schema. It says nothing about auth/permission requirements, rate limits, or how the API cap on limit behaves beyond the schema text.

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 no filler; the primary purpose is front-loaded before the return-shape detail. 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 parameterless-required read tool with no output schema, the description supplies the missing return-value information and confirms the filter scope, which is enough for correct invocation. It could go further by positioning itself against autowhisper_products_summary, but nothing critical is absent.

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 all four parameters (limit, workspace_id, include_archived, token) are already fully documented in the schema, including the important current-workspace default and token precedence. The description only alludes to workspace/archive filtering, adding no syntax or format detail beyond the schema, 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?

The description states a specific verb+resource (list products) and its scope (optional workspace/archive filters), which is clear. It does not, however, differentiate itself from the sibling autowhisper_products_summary, so an agent must infer the distinction from the name alone.

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 or when-not-to-use guidance, and the obvious alternative (autowhisper_products_summary) is never named or contrasted. 'Fast product list' hints at a lightweight enumeration use case but leaves routing 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 burden. It usefully discloses the return shape ('counts by workspace come with it') and that it is a cheap/fast read, but never states read-only semantics, auth expectations beyond the token param, or any rate limits.

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, front-loaded with the core capability and followed immediately by the routing rule. 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 simple count tool with no output schema and no annotations, the description tells the agent what it computes and roughly what it returns. It is nearly complete; only the read-only/auth profile is left implicit.

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 both parameters are already documented (including the important 'omit for CURRENT workspace, other workspaces NOT included' note). The description adds only the 'by account/workspace' scoping, which duplicates the schema; 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?

States a specific verb+resource+scope ('fast product counts by account/workspace'), which an agent can distinguish from autowhisper_products (full listing) and autowhisper_cmo. It does not explicitly name autowhisper_products as the sibling alternative, 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?

Gives an explicit trigger ('how many products do I have?') and routes away from a costlier alternative ('instead of spending a CMO chat turn'). Clear context, though it does not state when NOT to use it versus autowhisper_products.

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

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

With no annotations, the description carries the burden and does add real context: it is 'fast', it enumerates what is returned (products, feed, platforms, wallet, settings, workspace directory), and it declares that every count is scoped to the CURRENT workspace. It stops short of stating read-only behavior, auth/permission requirements, or error 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, front-loaded with the returned content and followed by the scoping caveat and sibling redirect. No filler or restated name/title.

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, and the description compensates by enumerating the returned sections plus the workspace directory. No annotations exist either, but the read-only nature is strongly implied by 'status'/'snapshot' and the remaining safety details are minor for a read 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 coverage is 100% so baseline is 3, but the description adds genuine cross-parameter meaning: it explains that the workspace directory (with ids) returned by this same tool is what should be supplied as workspace_id, tying the parameter to a concrete data source rather than leaving it abstract.

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 (a 'snapshot' of workspace products, feed, platforms, wallet, settings) and explicitly distinguishes scope from the sibling autowhisper_products_summary. An agent can tell what this does and what it is not without reading any 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?

Gives the primary use case (fast CMO/account snapshot for the current workspace) and routes to autowhisper_products_summary for account-wide product counts. It also implies the tool doubles as the source of other workspace ids, but does not state an explicit when-not-to-use beyond the one sibling call-out.

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 must carry the full behavioral burden. It only says 'Fast credit balance' and does not disclose whether the operation is read-only, what permissions are required, whether the balance is live or cached, or what happens on failure. The 'fast' adjective adds minor performance context but little behavioral substance.

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 redundant clauses. It is appropriately concise for a simple tool, though the word 'Fast' is mild marketing rather than essential instruction.

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 low-complexity tool with one fully described optional parameter and no nested objects, the description is minimally adequate. However, with no annotations and no output schema, it leaves the agent without information about return format or key behavioral expectations.

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 single optional parameter is fully documented in the schema. The description adds no parameter semantics, so the baseline of 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?

The description names a specific resource (credit balance for the account) and implies a fast retrieval operation. It is clear enough to understand what the tool does, but it does not explicitly distinguish itself from sibling tools such as autowhisper_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?

There is no guidance on when to use this tool versus alternatives, no stated prerequisites, and no exclusions. The agent is left to infer that it should call this when a credit balance is needed.

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