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by app.humantaste

arbitrate_dispute

Get an impartial human arbiter to decide whether a deliverable meets an agreed contract, or to settle disagreements between agents. Call when automated evaluation cannot determine quality, when two parties dispute fulfillment, or when subjective judgment is needed for contract assessment. Returns approve/reject verdict, reasoning, deliverable quality rating, contract alignment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional context. Use to clarify intent, constraints, audience, or anything that helps the expert evaluate.
termsUriNoWhere the att/v1 manifest is hosted (https/ipfs). Convenience only — the hash is the identity.
termsHashNoTerms anchor this dispute is bound to: keccak256 of the att/v1 terms manifest (as echoed from the x402 payment), or an opaque 32-byte document hash such as an LCP atrHash ("sha256:0x…" accepted). Persisted on the ruling for the receipt + precedent lookups.
termsJsonNoThe full att/v1 terms manifest object. If provided it must be a valid manifest whose keccak256 equals termsHash.
deliverableYesThe deliverable to assess. Text or a publicly accessible URL.
partyAPositionYesOne side of the dispute. The expert evaluates both impartially — order is arbitrary.
partyBPositionYesThe other side of the dispute.
contractDescriptionYesThe agreed contract or deliverable specification.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tipYes
statusYes
messageYes
offeringYes
priceUsdcYes
sessionIdYes

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description must fully disclose behavioral traits. It does disclose return values ('approve/reject verdict, reasoning, deliverable quality rating, contract alignment') and neutrality, but it omits operational implications such as cost, latency, or whether the ruling is binding. Thus it provides moderate transparency.

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 three sentences with front-loaded purpose, no redundant phrases, and each sentence serves a distinct function: what it does, when to call, and what it returns.

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?

The description is adequate for a complex tool with 8 parameters and an output schema. It covers the decision context and outcome, while the schema handles parameter details. It could mention any preconditions or asynchronicity, but overall it is sufficiently complete.

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%, so the baseline is 3. The description's narrative mentions 'deliverable' and 'contract' but does not add meaning beyond the schema's per-parameter descriptions.

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 function: 'Get an impartial human arbiter to decide whether a deliverable meets an agreed contract, or to settle disagreements between agents.' This specific verb and resource distinguish it from sibling tools like ask_a_human or consult_domain_expert by emphasizing impartial arbitration with a ruling outcome.

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 tells the agent when to invoke: 'Call when automated evaluation cannot determine quality, when two parties dispute fulfillment, or when subjective judgment is needed for contract assessment.' This is clear context, though it does not name alternatives or exclusion 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

A4.2/5.0
Disambiguation5/5

Each tool targets a specific action or domain, with clear distinctions between similar ones (e.g., review_content vs prepublish_review for different review purposes, order_think_tank_session_30 vs _60 by duration). No ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores, e.g., list_offerings, verify_certificate, request_human_approval. No mixing of conventions.

Tool Count4/5

17 tools is on the higher side but fully justified given the broad scope: expert consultations, think tanks, content reviews, verification, and human approval. Each tool serves a distinct purpose.

Completeness4/5

Covers the full workflow from discovery to ordering, revision, and on-chain verification. Minor gaps exist (e.g., no order cancellation or history listing), but core operations are well-represented.

Resources