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a2a2p — Agent-to-Agent-to-Physical

request_physical_solution

Submit a physical-world requirement (a part, product, device, or capability that must exist in the physical world). a2a2p resolves it and returns a RESOLUTION REPORT: a recommended path (best existing commercial solution vs. custom fabrication), pricing, tradeoffs, a delivery plan with contingencies and expedite options, and a business case when business context is provided. Response is asynchronous: you receive a request_id immediately with an instant spec_review. Poll check_request_status; as soon as an automated draft exists it is returned with an a2a2p.resolution-report-delivery receipt that distinguishes machine_draft from operator_published. If the finite attempt budget is exhausted, status returns generation_failed; if the bounded automatic retry window expires first, it returns generation_expired. Either terminal state permits only a new caller-confirmed request from caller-held input. Operator review and publication are not guaranteed or subject to a service-level promise. No state is professional engineering certification or a supplier quote.

ENTRY MODES — arrive with what you have: • fully_specified: provide 'specification' (part_type, material, process, dimensions, tolerance_class, design_files). Go straight to resolution report. • intent_only: provide 'intent' (purpose, environment, functional_requirements, quantity, timeline, priority). a2a2p recommends 2-3 specification options with tradeoffs. • partial: provide what you know in either layer; a2a2p fills the gaps.

Layer 1 (intent) describes the PROBLEM. Layer 2 (specification) describes the SOLUTION. At minimum, provide 'requirement' (legacy) or 'intent.purpose' (structured) — one line describing what you need. Use 'rejected_alternatives' to record options already ruled out.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intentNoLayer 1 — the problem. What the physical matter needs to DO. Use this for intent-driven requests where the agent describes purpose and a2a2p recommends solutions.
contactNoOptional email or callback endpoint for quote delivery.
deadlineNoRequired delivery date or timeframe. Maps to intent.timeline.
quantityNoNumber of units needed. Maps to intent.quantity.
budget_usdNoApproximate budget in USD. Maps to intent.budget_envelope.
constraintsNoHard constraints: tolerances, certifications, materials to avoid, size/weight limits. Maps to intent.functional_requirements.
requirementNoPlain-language description of the physical need. Maps to intent.purpose. Include function, dimensions, materials, load/performance requirements, environment, and interfaces where known.
callback_urlNoOptional HTTPS URL. When the quote is ready, a2a2p POSTs it as JSON to this URL.
specificationNoLayer 2 — the solution. What the physical matter IS. Populate what is known. Precise specifications produce faster, tighter quotes. Controlled vocabularies are preferred but open values are accepted.
business_contextNoOptional business requirements (expected volumes, cost targets, ROI constraints). If provided, the quote includes a business case.
rejected_alternativesNoOptions already considered and ruled out. Prevents re-suggesting and builds the learning corpus.

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden, and it substantially discloses behavior: async response with immediate request_id and spec_review, polling via check_request_status, machine_draft vs operator_published receipt distinction, and terminal states generation_failed and generation_expired. It also states that operator review/publication is not guaranteed and that output is not professional certification or a supplier quote.

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 long but structured into purpose, return protocol, and entry modes, with every section adding operational detail. It is slightly verbose and contains awkward phrasing like 'No state is professional engineering certifiation or a supplier quote,' which keeps it from being a 5.

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?

There is no output schema, yet the description explains the report's contents, async behavior, receipt states, and terminal statuses in enough detail for an agent to understand the full lifecycle. Combined with the richly documented input schema, the tool is effectively self-contained for invocation.

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?

Schema coverage is 100%, so the baseline is 3, and the schema already documents each field richly. The description adds cross-cutting meaning beyond the schema by establishing the layer model, the minium requirement (requirement or intent.purpose), and the role of rejected_alternatives, which helps an agent assemble a correct request.

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 first sentence names a specific verb and resource: 'Submit a physical-world requirement' and states that a2a2p resolves it and returns a RESOLUTION REPORT. This clearly distinguishes it from status-checking siblings like check_request_status and report- or simulation-oriented tools.

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

Usage Guidelines3/5

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

The description gives clear entry-mode guidance (fully_specified, intent_only, partial) and even routes the caller to check_request_status for polling, but it does not explicitly say when this tool should be preferred over siblings such as request_provider_estimate or build_supplier_request_package. Usage context is implied rather than contrasted.

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

A3.8/5.0
Disambiguation2/5

Multiple tool clusters have near-identical names and responsibilities: prepare_derived_beam_simulation, prepare_reviewed_beam_simulation, and prepare_simulation_study all produce bounded simulation studies, while the validate_* family has five variants with subtle input differences. The descriptions are detailed, but an agent would frequently need to read an entire paragraph to avoid misselection.

Naming Consistency5/5

All 24 tools follow the same snake_case verb_noun pattern: build_, check_, request_, validate_, prepare_, run_, upload_, etc. There are no camelCase names, no vague single-word tools, and no stylistic outliers.

Tool Count3/5

24 tools is at the heavy end of the calibration range, and a large subset of rectangular-beam preparation/validation tools could be consolidated. The broad physical-request and supplier pipeline justifies some of the count, but the overall surface still feels over-scoped.

Completeness4/5

The core workflows are covered: upload, submit, revise, status, spec review, pricing/estimates, quote-job polling, supplier package/email rendering, and a full bounded simulation loop. Missing cancellation, request listing, and actual supplier send/order actions are real but peripheral gaps rather than workflow-killing dead ends.

Resources