Sync by CHNLSYNC

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description discloses important behavior: a private advisor workspace is created on the first call, credentials are returned, and replies never contain supplier names or pricing until a human broker review. It also specifies the claim_url/callback path, giving the agent a realistic model of side effects and limitations.

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 front-loaded with the core purpose and then presents the stateful calling convention in a clear, ordered sequence. Every sentence adds necessary operational detail, and there is no filler or repetition. The line break separates the high-level purpose from the concrete protocol, improving scannability.

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?

The description fully covers the multi-turn workflow: how to start, how to continue, what to persist, and what to expect in replies. The only minor issue is mentioning 'conversation_id' as a value to persist without clarifying that it is not an input parameter and likely appears in the response, which could cause slight confusion for an agent.

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?

With 0% schema description coverage, the description compensates well by explaining the roles of company_name, pain, session_id, and session_token. It clarifies that pain is a plain-language description of what is not working. The one gap is that 'message'—the only required parameter—is not explicitly defined, though its purpose is reasonably inferable from the advisor context.

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 first sentence states a clear, specific action—'Consult CHNLSYNC's advisor about the user's IT environment'—identifying both the resource (the advisor) and the subject (IT environment). This distinguishes the tool from its siblings, which focus on retirement checks and broker callbacks. The purpose is explicit and not a tautology.

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 provides explicit usage context: first call must omit session_id/session_token and include company_name plus pain, while later calls must pass session_id/session_token. It also instructs persisting these values across turns. However, it does not mention when not to use this tool or contrast it with sibling alternatives, so it stops short of full 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?

The readOnlyHint annotation already signals a safe read operation. The description adds meaningful behavioral context beyond that: the operation is deterministic, the underlying dataset is FCC-sourced with a CC BY 4.0 license, and the returned source_url must be cited. This is genuinely useful transparency for an agent.

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 compact sentences with no filler. The core purpose is front-loaded, the citation requirement is stated early, and parameter guidance is efficiently embedded. Every sentence 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 read-only lookup tool with two optional parameters and an output schema, the description covers everything an agent needs: what the tool does, how to format inputs, the full-dataset behavior, data provenance, and citation obligations. No significant usage gap remains.

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 for parameter semantics. It compensates well by explaining 'carrier' accepts display names like 'AT&T', 'Lumen', 'Frontier', that 'state' is a two-letter abbreviation, and that both can be omitted for the full dataset. It stops short of listing all accepted values or matching rules, but it gives enough guidance for correct invocation.

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 verb ('Look up'), a precise resource ('US copper/POTS retirement program status'), and the filtering dimensions ('by carrier and state'). It also identifies the authoritative dataset (CHNLSYNC's FCC-sourced data), making the tool's purpose unambiguous and clearly distinct from the unrelated sibling tools.

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

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

The description gives clear context on how to use the tool: carrier accepts display names, state is a two-letter abbreviation, and omitting both returns the full dataset. It does not explicitly state when not to use it or name an alternative, but the sibling tools are sufficiently unrelated that no exclusion is necessary.

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?

The description discloses key behavioral traits beyond annotations: the callback is already queued, a broker will reach out regardless of booking, and the book_url is optional. It also discloses the privacy-sensitive side effect of sharing the user's name and email with CHNLSYNC.

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 concise and front-loaded with the core purpose, followed by necessary preconditions and result-handling guidance. Each sentence adds actionable information with no filler or repetition of the schema.

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?

The description is complete for a tool with a visible output schema and minimal annotations: it covers purpose, prerequisites, consent requirements, side effects, and how to handle the result. No critical operational detail is missing for an agent to invoke this 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 0%, so the description must compensate for all four parameters. It effectively does so by mapping session_id/session_token to 'session credentials returned by ask_sync_advisor' and contact_name/contact_email to the name and email shared with consent. It does not name the parameters explicitly, but the mapping is clear enough.

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 and resource: 'Ask a CHNLSYNC human broker to contact the user.' It clearly differentiates this from ask_sync_advisor by stating that it requires the session credentials returned by that sibling, making the workflow relationship 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 description gives explicit conditions: only call with the user's explicit consent, and only after obtaining credentials from ask_sync_advisor. It also instructs the agent not to present the booking link as required, which prevents a common misuse of the tool.

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