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AI Design Blueprint Doctrine

Request Operator Handoff

handoffs.operator

Authenticated — creates a support handoff record when an agent needs human review, account-specific escalation, or operator follow-up that cannot be resolved with the read-only doctrine tools. Persists a SupportHandoff row (reason, topic, page_url, agent_name, agent_platform, trace_summary, user_email) routed to the support inbox; user is contacted by the team. WHEN TO CALL: user explicitly asks for human help, hits a billing/access issue, or the agent has tried the doctrine tools and the user still needs a human. ALWAYS confirm with the user before firing — this creates a human-visible ticket. WHEN NOT TO CALL: proactively, silently, or to log debugging traces (use diagnostic logs instead); for partnerships/agency enquiries (use handoffs.partnership / handoffs.agency); for content questions answerable by principles.search / guides.search. BEHAVIOR: write-only, single insert, side-effecting (creates a ticket the team will see). Auth: Bearer (any plan). UK/EU residency. Response confirms ticket id + topic so the user can reference it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNoTopic category for routing (e.g. 'agent', 'billing', 'access', 'general').agent
localeNoResponse locale for the handoff acknowledgment.en
reasonYesClear description of why a human operator review is needed.
page_urlNoURL of the page or context where the handoff was triggered.
agent_nameNoName of the agent or client triggering the handoff.mcp-client
trace_summaryNoOptional summary of the agent's recent actions or trace for operator context.
agent_platformNoPlatform or runtime the agent is running on (e.g. 'claude-code', 'cursor', 'copilot').

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses that the tool is write-only, single insert, side-effecting (creates a human-visible ticket). It also reveals auth requirements (Bearer token, any plan), residency (UK/EU), and response behavior (confirms ticket id + topic). These details go beyond the annotations (readOnlyHint=false, openWorldHint=true) and provide a clear behavioral model.

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 well-structured: starts with overall purpose, then provides clear WHEN TO CALL/WHEN NOT TO CALL sections, followed by behavioral notes and auth. Every sentence serves a purpose, and the key action (create ticket, confirm with user) is front-loaded. It is appropriately sized for the tool's complexity.

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 the tool has 7 parameters, annotations, and an output schema, the description covers all critical aspects: purpose, usage boundaries, behavior, auth, residency, and response format. It leaves no major gaps for an agent to make incorrect calls. The presence of an output schema (not shown) allows the description to focus on usage and behavioral context.

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

Parameters4/5

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

Input schema has 100% description coverage, so the baseline is 3. The description adds value by listing the fields persisted (reason, topic, page_url, etc.) and clarifying that user_email is auto-populated (not in input schema), which aids understanding. However, it does not elaborate on each parameter beyond the schema, so a modest uplift is justified.

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 creates a support handoff record for human review, with specific use cases. It distinguishes from sibling tools handoffs.partnership and handoffs.agency, and from other tools like principles.search and guides.search, by providing explicit WHEN NOT TO CALL directives.

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 WHEN TO CALL conditions (user asks for human help, billing/access issues, after trying doctrine tools) and WHEN NOT TO CALL conditions (proactive/silent calls, logging, partnerships/agency queries, content questions). It also instructs to confirm with user before firing, giving clear decision criteria.

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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TDQS

A4.6/5.0
Disambiguation5/5

Each tool targets a clearly distinct purpose. For example, architect.validate vs architect.validate_consensus differ in single-shot vs consensus; handoffs.agency, handoffs.operator, and handoffs.partnership are separated by engagement type. No significant overlap.

Naming Consistency4/5

Tools follow a consistent dot-notation grouping (architect.*, clusters.*, examples.*, guides.*, handoffs.*, me.*, principles.*, signals.*, team.*) with predictable verbs (validate, list, get, search, add, etc.). Minor deviation: some underscore within names (e.g., me.add_evidence) but overall pattern holds.

Tool Count4/5

24 tools is on the higher side but justified given the broad domain spanning validation, certification, learning, handoffs, and feedback. Each tool has a clear role, and the count reflects the platform's comprehensive scope without feeling bloated.

Completeness5/5

The tool surface covers the full workflow (validate → consensus → certify), discovery (principles, clusters, examples, guides), personal progress (learning path, coaching, evidence), handoffs (support, partnership, agency), feedback, and team summaries. No obvious gaps for the stated purpose.

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