Skip to main content
Glama

testimonial_request_email

Write a warm, non-pushy email asking a past or current client for a testimonial, case study, or LinkedIn recommendation. Includes a specific angle prompt to help them respond without a blank page.

Instructions

Write a warm, non-pushy email asking a past or current client for a testimonial, case study quote, or LinkedIn recommendation. Sent after a successful delivery or project milestone. Includes a specific angle or prompt to make it easy for the client to say yes without staring at a blank page. Distinct from client_offboarding_checklist_email (which only has a brief optional postscript ask) — this is a standalone, full-effort ask with a tailored hook. Does not count against your monthly draft limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
client_nameYesThe client's first name or company name
project_nameYesName of the project or work completed (e.g. 'the Acme website redesign', 'our 6-month SEO retainer')
result_achievedYesA specific positive outcome the client got from the work (e.g. '40% increase in organic traffic', 'launched on time and under budget', 'closed three new clients using the proposal templates we built'). Be concrete — the more specific, the easier the ask.
testimonial_typeNoOptional: what you're asking for — 'testimonial' (for your website), 'linkedin_recommendation', 'case_study', or 'google_review'. Defaults to 'testimonial'.
angle_promptNoOptional: a specific question or angle to guide the client (e.g. 'what problem you were trying to solve before we started', 'what surprised you about working together', 'how you'd describe the ROI to a peer'). Providing this makes the ask far easier to fulfil.
your_nameNoOptional: your name for the sign-off
Behavior4/5

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

With no annotations, the description carries the burden. It describes the tone ('warm, non-pushy'), the content structure (includes angle/prompt), and the draft limit behavior. However, it doesn't explicitly state whether the tool sends the email or just drafts it, though context implies drafting.

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 reasonably concise and front-loaded with the core action. It is a single paragraph, which could be more structured, but it effectively conveys key information without unnecessary words.

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

Completeness4/5

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

Given the lack of output schema and annotations, the description is fairly complete. It explains the tool's purpose, usage timing, and a unique behavioral feature. It doesn't describe the return value, but for a generation tool this is usually acceptable.

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

Parameters3/5

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

Schema description coverage is 100% with high-quality descriptions. The tool description adds marginal value, e.g., reinforcing that 'result_achieved' should be concrete and that 'angle_prompt' makes the ask easier. This meets the baseline but doesn't significantly enhance understanding beyond the schema.

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's purpose: 'Write a warm, non-pushy email asking a past or current client for a testimonial, case study quote, or LinkedIn recommendation.' It uses specific verbs and resources, and explicitly distinguishes itself from the sibling 'client_offboarding_checklist_email'.

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 provides explicit usage context: 'Sent after a successful delivery or project milestone.' It clearly distinguishes this tool from the sibling 'client_offboarding_checklist_email', stating this is a standalone, full-effort ask. It also includes a behavioral note about not counting against draft limits.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jabbawocky/proposalcraft'

If you have feedback or need assistance with the MCP directory API, please join our Discord server