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Contract Testing: Publish Provider Contract

contract-testing_publish_provider_contract
Idempotent

Publish a provider OpenAPI contract and its self-verification results to PactFlow for bi-directional contract testing.

Instructions

Publish a provider OpenAPI contract and self-verification results to PactFlow (Bi-Directional Contract Testing).

Toolset: Contracts

Parameters:

  • providerName (string) required: Name of the provider application

  • pacticipantVersionNumber (string) required: Version number of the provider

  • contract (object) required: Provider contract (OpenAPI spec) and verification details

  • tags (array): Version tags

  • branch (string): Branch name of the provider

  • buildUrl (string): URL of the CI build

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoVersion tags
branchNoBranch name of the provider
buildUrlNoURL of the CI build
contractYesProvider contract (OpenAPI spec) and verification details
providerNameYesName of the provider application
pacticipantVersionNumberYesVersion number of the provider
Behavior2/5

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

Annotations indicate idempotentHint=true and destructiveHint=false, which align with a publish operation. However, the description does not disclose important behaviors such as whether publishing overwrites existing contracts, authentication requirements, or potential side effects (e.g., triggering verifications). The description adds minimal value beyond the annotations.

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 at two paragraphs, front-loading the purpose. However, listing parameters duplicates the schema, which is unnecessary and adds length. Still, it remains relatively efficient and readable.

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

Completeness2/5

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

The description lacks details about the return value or success/failure indication, which is needed since no output schema exists. It also does not clarify idempotency behavior or required permissions, leaving gaps for an AI agent selecting this tool. For a complex write operation with nested objects, more context is expected.

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%, meaning the schema already defines all parameters and their purposes. The description lists parameters but repeats the schema descriptions without adding new insights or usage constraints (e.g., format requirements for the nested contract object). Baseline score of 3 appropriate given high coverage.

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 action ('Publish a provider OpenAPI contract and self-verification results') and specifies the target system (PactFlow for Bi-Directional Contract Testing). It effectively distinguishes from sibling tools like contract-testing_publish_consumer_contracts.

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 mentions the toolset (Contracts) but does not explicitly state when to use this tool versus alternatives (e.g., publish_consumer_contracts). No 'when not to use' or preconditions are provided, leaving the agent to infer usage from the purpose.

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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