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x_api_like_post

Like a post on X using the X API. Provide the post ID and OAuth user credentials to perform the action.

Instructions

Like Post. Use when: Like Post. Do not use when: a more specific auth/configuration tool is required before the API call or you are only exploring; prefer x_schema_discovery or x_query_suggestion first. Risk: mutating, high-risk. Required permissions and prerequisites: OAuth 2 user token with scopes like.write, tweet.read, users.read; OAuth 1a user token Environment-selection behavior: scopeTenantId plus exactly one of scopeUserId or scopeAccountId choose the Vault/Postgres tenant principal used for auth resolution. credentialKey selects a non-default stored credential profile when present. Parameter formats and constraints: id (path, unknown, required); body is used for the documented request payload. Expected response shape: { ok, status, data: { method, path, url, status, contentType, authType, data } } Common failure conditions: missing scoped credentials in Vault, missing required API parameters, X API auth failures, rate limits, or unsupported multipart/body shape. Recommended prerequisite and follow-up tools: x_connection_info, x_schema_discovery, x_auth_upsert_principal_credentials, x_api_request. Safety warnings: This mutates X state. Validate scope, payload, and authorizationKey before use. Example: {"name":"x_api_like_post","arguments":{"scopeTenantId":"default","scopeUserId":"default","id":"","body":{}}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
bodyNo
scopeUserIdNo
credentialKeyNo
scopeTenantIdNo
scopeAccountIdNo
authorizationKeyNo
preferredAuthTypeNo
Behavior5/5

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

With no annotations, the description fully carries the burden of behavioral disclosure. It explicitly states 'Risk: mutating, high-risk,' required OAuth scopes, environment-selection behavior, expected response shape, common failure conditions, and safety warnings. This is comprehensive transparency beyond the structured data.

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 well-structured with labeled sections, making it scannable. It avoids fluff but is somewhat repetitive (e.g., 'Like Post' appears in the opening and in 'Use when'). Overall, the density of useful information justifies a score above average, though it could be tightened.

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?

This is a mutating, high-risk tool with 8 parameters and no output schema, yet the description covers required permissions, environment behavior, parameter roles, response shape, failure conditions, and even provides an example invocation. It leaves little uncovered for an agent to invoke the tool correctly.

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?

Given 0% schema description coverage, the description adds meaningful semantics for key parameters: 'id (path, unknown, required)' and 'body is used for the documented request payload.' It also explains how scopeTenantId, scopeUserId, scopeAccountId, and credentialKey work together for auth resolution. However, it does not explain authorizationKey or preferredAuthType in detail, leaving some gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Like Post,' which clearly identifies the action and resource, but it does little more than restate the tool name and does not explicitly distinguish this from sibling tools like x_api_unlike_post or x_api_get_posts_liking_users. The overall purpose is unambiguous, but the differentiation relies on the tool name rather than the description.

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 includes explicit 'Use when' and 'Do not use when' guidance, including concrete alternatives: 'prefer x_schema_discovery or x_query_suggestion first' when exploring. This satisfies the requirement for clear usage context and exclusions, earning a top score.

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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