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AI Design Blueprint Doctrine

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handoffs.agency

Submit an agency engagement enquiry for a founder-led discovery call. Choose from four scopes: workflow sprint, proof-of-concept, pilot support, or advisory. Get hands-on expert support beyond self-service learning.

Instructions

Submit an agency engagement enquiry on behalf of the authenticated user for a founder-led discovery call. Agency engagements cover four scopes: workflow sprint (rapid agentic workflow implementation), proof-of-concept (validate a specific agent design in a bounded timeframe), pilot support (co-design and validate a production-ready pilot), and advisory (ongoing architectural guidance across a product team). Use this when the user has identified a need for hands-on expert support beyond self-service learning. Requires a Firebase Bearer token.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYesDescription of the engagement need: workflow sprint, proof-of-concept, pilot support, or advisory.
companyNoCompany or team name submitting the agency inquiry.
roleNoRole or title of the person submitting the agency inquiry.
workflow_stageNoCurrent workflow stage.
support_typeNoType of support needed.
websiteNoWebsite or relevant URL for the team or project.
agent_nameNoName of the agent or client triggering the handoff.mcp-client
agent_platformNoPlatform or runtime the agent is running on.
trace_summaryNoOptional agent trace summary for operator context.
localeNoResponse locale for the acknowledgment.en
Behavior4/5

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

Annotations already indicate this is a write, non-idempotent, open-world operation. The description adds behavioral context by requiring a Firebase Bearer token, which is beyond annotations. It does not contradict annotations, and the token requirement is a useful transparency addition.

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 concise (7 sentences), front-loaded with the core action, and each sentence serves a purpose. Some redundancy exists because scope details are repeated from the schema, but overall it is well-structured and avoids unnecessary fluff.

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

Completeness3/5

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

Given 10 parameters, 1 required, and no output schema, the description adequately explains the tool's purpose and usage. However, it does not describe the response or error scenarios, leaving some ambiguity about what happens after submission. This gap prevents a higher score.

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 coverage is 100%, so baseline is 3. The description explains the four scope definitions (workflow sprint, proof-of-concept, pilot support, advisory) which corresponds to the reason parameter, but this is already detailed in the schema. It adds minimal new meaning beyond what the schema provides.

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 verb (submit an enquiry), resource (agency engagement enquiry), and context (founder-led discovery call). It distinguishes the tool from siblings by specifying the scope of agency engagements (workflow sprint, proof-of-concept, pilot support, advisory), making its purpose unambiguous.

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 explicitly states when to use: 'when the user has identified a need for hands-on expert support beyond self-service learning.' It provides context but does not explicitly exclude other scenarios or mention alternative tools by name. The sibling names imply alternatives, but the description lacks direct comparison.

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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