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discovery_call_no_show_email

Craft a professional follow-up email when a prospect misses a scheduled discovery call. Adjusts tone for first no-show (reschedule) or second no-show (polite close-out).

Instructions

Write the email to a prospect who booked a discovery call and didn't show up. One of the most common and awkward freelancer situations — you cleared the time, they ghosted, and now you have to decide how to handle it. Gets the tone right: not passive-aggressive, not a pushover, not grovelling. First no-show: assumes good faith (tech issues, genuine emergency) and offers a single, low-friction reschedule. Second no-show: politely closes the door while leaving it ajar if they ever do want to proceed. Distinct from meeting_cancellation_email (you cancel), meeting_postponement_email (you postpone), and cold_pitch_follow_up (prospecting). Does not count against your monthly draft limit. Required: client_name. Optional: call_time (e.g. 'today at 2pm', 'Monday at 10am') — adds specificity, no_show_count (1 or 2 — defaults to 1 for first no-show, 2 gives the close-out version), reschedule_link (e.g. 'my Calendly link', 'cal.com/yourname' — defaults to replying to the email), your_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_nameYesFirst name or full name of the prospect
call_timeNoOptional: when the call was scheduled (e.g. 'today at 2pm', 'Monday at 10am', 'this morning at 9')
no_show_countNoOptional: 1 for first no-show (give benefit of the doubt, offer reschedule — default), 2 for second no-show (polite close-out)
reschedule_linkNoOptional: how to rebook (e.g. 'my Calendly link: cal.com/yourname', 'this link: calendly.com/you'). Defaults to replying to the email.
your_nameNoOptional: your name for the sign-off
Behavior4/5

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

The description explains the behavioral logic: assumes good faith on first no-show offers reschedule, and politely closes on second no-show. However, it does not explicitly state whether the tool sends the email directly or outputs draft text, leaving a minor ambiguity about its exact action.

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

Conciseness5/5

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

The description is concise and well-structured: starts with core purpose, adds context, differentiates from siblings, and lists parameters with defaults. Every sentence adds value without redundancy.

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

Completeness5/5

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

Given no output schema and few sibling complexities, the description covers purpose, usage, parameters, and behavioral nuances comprehensively. It even notes the draft limit exemption, which adds helpful context.

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

Parameters5/5

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

With 100% schema coverage, the baseline is 3, but the description adds substantial meaning with examples (e.g., call_time: 'today at 2pm', no_show_count: defaults and scenario outcomes, reschedule_link: default behavior). This goes well beyond the schema descriptions.

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

Purpose5/5

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

The description clearly states the tool writes an email to a prospect who missed a discovery call. It explicitly distinguishes from siblings like meeting_cancellation_email, meeting_postponement_email, and cold_pitch_follow_up, and outlines the two scenarios (first no-show vs second no-show).

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool vs alternatives by naming siblings and their contexts. It also notes that it does not count against a monthly draft limit, providing additional usage guidance.

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

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