LetsAskIt

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

Annotations already disclose the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=false), so the burden is reduced. The description adds that output is a 'finished multi-format content pack', but says nothing about whether the operation is asynchronous or returns a job id (hinted by the get_job_status sibling), nor about format defaults or 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 with zero waste; the core action is front-loaded before the shorthand note. 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 three-parameter write tool with no output schema and low schema coverage, the description is sufficient to identify the tool but not to invoke it confidently. It omits how formats are selected/defaulted and whether the result is returned directly or via polling get_job_status.

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 only 33% (only 'transcript' is documented), so the description should compensate. It vaguely implies multi-format output but never mentions the 'formats' enumerations or 'voice_profile_id', leaving two undocumented parameters entirely unclarified.

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

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

States a specific verb and resource ('Create a finished multi-format content pack') and immediately scopes the input source ('from a meeting or call transcript'). It also distinguishes itself from the create_pack sibling by naming the exact shorthand relationship (input_type=transcript).

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 'shorthand for create_pack with input_type=transcript' line gives clear routing context for choosing between this and create_pack. It does not explicitly contrast with create_from_url or state when not to use it, but the transcript input is self-evident from the purpose statement.

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 openWorldHint=true, idempotentHint=false, and readOnlyHint=false, so external-fetch and non-idempotent semantics are covered structurally. The description usefully confirms the fetch-and-extract behavior, but says nothing about async job behavior, permissions, or rate limits — notable given the sibling get_job_status implies polling.

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 load-bearing: the first defines the operation, the second routes against the sibling. Nothing redundant and the action verb 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?

For a 3-parameter creation tool with no output schema, the description omits the async/job lifecycle (get_job_status exists as a sibling for a reason) and leaves two parameters unexplained. It covers the core operation adequately but not everything an agent needs to call it confidently.

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 33%: url is documented in-schema, but formats and voice_profile_id have no description anywhere. The phrase 'multi-format' hints at the formats parameter but adds no enumeration, defaults, or relation to voice_profile_id, so the description 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?

States a specific verb chain (fetch, extract, create) and resource (multi-format content pack), and explicitly distinguishes itself from the sibling create_pack by naming the shorthand equivalence with input_type=url. An agent can route between create_from_url, create_pack, and create_from_transcript without opening schemas.

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 'shorthand for create_pack with input_type=url' clause gives a clear usage rule and implicitly tells the agent when the generic sibling is unnecessary. However, it gives no exclusions (e.g., when a URL is not fetchable, or when to prefer transcript-based input).

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 write (readOnlyHint=false), non-idempotent, non-destructive, open-world. The description adds valuable context beyond them: the completed pack carries a visible quality gate (voice match, factual flags, platform fit). However, it omits whether the call returns synchronously or hands off to a job (the get_job_status sibling strongly implies async), plus any cost or failure behavior, so it only partly fills the gap.

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

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

A single dense sentence, front-loaded with the verb and the deliverable, then the accepted sources. No filler or repetition of the schema. It is slightly overpacked (output list plus quality-gate parenthetical) but earns its length.

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, describing the returns (each piece plus its quality gate) is the right move and it does so. But for a write, open-world, non-idempotent tool it leaves out sync-vs-async execution, what happens on partial format failure, and how it relates to get_job_status and the two specialized create siblings, leaving the agent to infer key operational behavior.

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

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

Schema description coverage is 100%, so the schema already defines content, input_type, formats, and voice_profile_id semantics (including the list_voice_profiles reference). The description adds marginal meaning by tying voice_profile_id to 'the caller's brand voice,' but no syntax, defaults, or format-selection guidance beyond 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 (create) and resource (multi-format content pack), enumerates the exact outputs (LinkedIn post, X thread, newsletter section, SEO article, summary) and the accepted input forms. This is far more specific than a tautology. It stops short of 5 because it never contrasts itself with the sibling tools create_from_transcript and create_from_url, which overlap heavily with two of the listed input types.

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 versus when-not-to-use guidance. The description lists accepted inputs (transcript, URL) that are covered by dedicated siblings (create_from_transcript, create_from_url) without telling the agent which tool to prefer, and it never mentions get_job_status despite the write/open-world annotations implying a long-running job. Only implied usage is available.

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

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds one useful behavioral nuance – that the finished pack only exists 'when done', i.e. results may be partial – but says nothing about auth needs, error states for an unknown/expired job id, or retention.

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 tightly packed sentence that front-loads the verb and resource and appends the return contents. Every clause carries information; 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?

With no output schema, the description correctly takes on the burden of describing the return payload (status, input, finished pack, per-piece quality gates), which is what an agent needs. It omits failure modes such as a missing or expired job id, leaving a small gap.

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

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

Schema description coverage is 100% and there is a single parameter, so the schema already documents job_id ('The job id from create_*'). The description only restates 'by id' and adds no format, source, or validation detail beyond the schema, 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?

The description uses a specific verb ('Fetch') plus resource ('a creation job by id') and enumerates the returned payload (status, input, finished pack, quality gates). It is clearly distinct from the create_* siblings, though it never names them or explicitly contrasts itself with them, so it falls short of the 5 benchmark.

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

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

Usage is only implied: the parenthetical '(when done)' signals this is a polling/status-check tool to call after create_from_transcript, create_from_url, or create_pack. There is no explicit statement of when to call it, how often to poll, or what to do if the job is not finished.

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 safety disclosure is covered and the bar is lower. The description adds genuine value beyond the annotations by disclosing the shape of the result (id, name, sample count) and the relationship to the create_* tools. It omits ordering/pagination behavior, keeping it short of 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?

A single sentence with no filler, front-loaded with the verb and resource and ending with the useful cross-tool linkage. Every clause earns its place.

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

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

For a zero-parameter list tool with rich read-only annotations, the description covers identity, the consuming tools, and the returned fields in lieu of an output schema. It stops short of stating whether all profiles are always returned or how they are ordered, a minor remaining gap.

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

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

The tool takes zero parameters, which is the baseline-4 case; there are no parameter semantics to explain. The description does not need to add anything here and correctly refrains from inventing options.

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

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

States a specific verb ('List') and a precisely-scoped resource ('saved brand voice profiles'), and even names the returned fields. It also distinguishes itself from siblings by noting these profiles are the inputs consumed by the create_* tools, so an agent can tell it apart from the create/get tools immediately.

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

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

The phrase 'available for the create_* tools' implies this is a lookup to perform before invoking create_from_transcript/create_from_url, which is meaningful workflow context. However, it never explicitly says when to call it, when not to, or what to do with the result, so usage remains implied rather than stated.

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