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work_sample_response_email

Draft a professional email to respond to a prospect's request for work samples, either sharing relevant examples or acknowledging gaps with adjacent work and a next step.

Instructions

Write a professional email responding to a prospect who has asked to see work samples or portfolio pieces before deciding whether to hire you. Two modes: have_samples (default — you have directly relevant work to share; links or describes the samples with brief context on why they're relevant to this client's situation), no_exact_match (you don't have a perfect example in this specific niche or format, but you have closely adjacent work that demonstrates the same underlying skill; acknowledges the gap honestly without being apologetic, explains what the adjacent work shows, and offers a next step — call, test piece, or scoped pilot). The no_exact_match mode is often more persuasive than it sounds: handled well, it signals integrity and directness. Required: client_name. Optional: project_context (what the prospect is evaluating you for — makes the email specific rather than generic), sample_description (one-line description of what you're sharing or linking — e.g. 'three brand strategy decks for similar-scale clients', 'a website redesign for a professional services firm'), sample_link (direct URL or 'attached' — if omitted, email offers to send on request), adjacent_work (for no_exact_match mode: what you have that's adjacent — e.g. 'I haven't done X specifically, but here are two projects where I did Y under the same constraints'), next_step (what you're proposing after the sample review — e.g. 'happy to jump on a 20-minute call', 'I can put together a short test piece'), your_name. Does not count against your monthly draft limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_nameYesProspect's first name
project_contextNoOptional: what they're evaluating you for — makes the email feel specific. E.g. 'the brand identity project', 'the content retainer', 'rewriting your website copy'.
sample_descriptionNoOptional: one-line description of what you're sharing — e.g. 'three brand strategy decks for professional services clients', 'a UX audit and redesign for an e-commerce site'.
sample_linkNoOptional: URL to portfolio or samples, or 'attached' if sending as a file. If omitted, the email offers to send on request.
adjacent_workNoOptional (used in no_exact_match mode): what closely adjacent work you have — e.g. 'I haven't done fintech specifically, but I've worked on three regulated-industry brands where the same constraints applied'. Be specific.
response_modeNohave_samples (default — you have directly relevant work to share), no_exact_match (you don't have a perfect match but have adjacent work that demonstrates the same skill).
next_stepNoOptional: what you're proposing after the sample review — e.g. 'happy to jump on a 20-minute call to walk through them', 'I can put together a short test piece if that would help'.
your_nameNoYour name for the sign-off
Behavior4/5

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

With no annotations provided, the description fully discloses the tool's behavior: it can generate emails in two modes, and the sample_link parameter controls whether links are included or offered upon request. The description also clarifies that the tool does not consume a monthly draft limit, which is a behavioral trait not evident from the schema alone.

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

Conciseness4/5

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

The description is lengthy but well-structured, with a clear opening sentence followed by detailed explanations of modes and parameters. It uses bullet-like formatting for parameter descriptions, aiding readability. While it could be slightly trimmed, every section adds value and is well-integrated.

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?

The description covers all necessary aspects: purpose, modes, parameter semantics, and a behavioral note about draft limits. Given the lack of an output schema, it conceptually describes the output as a professional email. The description is comprehensive for the tool's complexity and adequately prepares the agent to use it effectively.

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?

The description adds substantial meaning beyond the 100% schema coverage. It explains how each optional parameter enhances specificity, provides examples for sample_description, adjacent_work, and next_step, and clarifies the role of response_mode. This contextual information helps the agent craft highly tailored emails.

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 explicitly states the tool's purpose: writing a professional email responding to a prospect requesting work samples or portfolio pieces. It distinguishes two clear modes (have_samples and no_exact_match) and notes that it doesn't count against the monthly draft limit, setting it apart from sibling tools like cold_pitch or proposal_to_email.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use each mode, with detailed explanations of the default (have_samples) and the alternative (no_exact_match). It explains the persuasive value of the no_exact_match mode. However, it lacks explicit 'when not to use' guidance or alternatives for other scenarios, such as when the prospect hasn't requested samples.

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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