Install Jentic One Beta
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Hastewire API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhastewire.com%2Fhastewire" | shStep 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fhastewire.com%2Fhastewire" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with Hastewire API.
Humanize a block of AI-generated text into a more natural version
Detect how AI-written a passage of text appears
Read the account behind the API key
Read billed usage for the account
Check the service status before running a batch
GET STARTED
Patterns agents use Hastewire API for, with concrete tasks.
★ Humanize Then Detect
An agent reworks AI-generated copy and verifies the result. It sends the draft to the humanize operation, takes the reworked text, then sends that text to the detect operation to score how AI-written it still reads. Because humanize and detect are separate operations, the agent can loop: rewrite, re-score, and stop when the detection score is low enough.
Send an AI-generated draft to the humanize operation, then send the result to the detect operation and return both the text and its score
Content Pipeline Gate
An agent gates a publishing pipeline on an AI-likelihood check. It runs the detect operation on each draft and only lets passages below a chosen threshold through, routing the rest back to be humanized. This gives an editorial workflow an automated check without a human reading every draft first.
Run the detect operation on a draft and return whether its AI-likelihood score is above or below a given threshold
Usage-Aware Batches
An agent keeps a humanizing batch within budget. It reads billed usage and the account before a run, confirms the service status, then processes drafts while watching consumption. Because usage is its own endpoint, a scheduled agent can pause itself when it nears a limit rather than failing mid-batch.
Read billed usage and service status, then humanize a batch of drafts only while usage stays within budget
5 endpoints — the hastewire api rewrites ai-generated text to read more naturally and scores text for how ai-written it looks.
METHOD
PATH
DESCRIPTION
/api/v1/humanize
Humanize AI-generated text
/api/v1/detect
Detect AI-generated text
/api/v1/status
Check the service status
/api/v1/me
Read the account behind the API key
/api/v1/usage
Read billed usage for the account
/api/v1/humanize
Humanize AI-generated text
/api/v1/detect
Detect AI-generated text
/api/v1/status
Check the service status
/api/v1/me
Read the account behind the API key
/api/v1/usage
Read billed usage for the account
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Hastewire by hand means handling its bearer API key, tracking prepaid credit usage, and checking service status before a batch. Through Jentic you install once, import Hastewire from the API Directory, store the key once, and your agent calls it.
Permission scoping
Hastewire sends the text to process in the request body, not the URL, so a rule bounds which operations your agent may call rather than which text it touches. You choose the operations it may use, such as humanize and usage, so the detect operation stays off until you add it.
Credential isolation
Your Hastewire API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'humanize AI text' or 'detect AI writing', and Jentic returns the matching Hastewire operation with its input schema so the agent calls the right endpoint without reading the reference docs.
Alternatives and complements available in the Jentic catalogue.
Specific to using Hastewire API through Jentic.
What authentication does the Hastewire API use?
Per its OpenAPI spec, the Hastewire API authenticates with a bearer API key in the Authorization header, while the service-status endpoint is open. Through Jentic the key is stored by your own self-hosted instance and injected when the agent calls the humanize, detect, account, or usage operations, so it never appears in the agent's prompt or logs.
Can I humanize and detect AI text with the Hastewire API?
Yes. The humanize operation reworks a block of AI-generated text into a more natural version, and the detect operation scores how AI-written a passage appears. An agent can chain them: humanize a draft, then run detect on the result to check the score, and repeat until it is satisfied.
What are the rate limits for the Hastewire API?
The OpenAPI spec does not state a numeric rate limit; requests are billed in prepaid credits, and the usage endpoint lets an agent track its own consumption. Add backoff around 429 responses, and check the Hastewire documentation at https://hastewire.com for current limits and pricing.
Can I limit what my agent is allowed to do with the Hastewire API?
Yes. Hastewire sends the text to process in the request body rather than in the URL, so a rule bounds which operations your agent may call, such as humanize and detect, not which text it processes. You choose that it may humanize and read usage while the detect operation stays off until you add it, and every call it makes is logged.
Is there a Hastewire MCP server?
You do not need an MCP server to give your agent the Hastewire API. Jentic connects it directly from the Jentic API Directory: import Hastewire, store your API key once, and your agent calls the humanize and detect operations on demand without loading another server's tool definitions into its context.
How do I humanize text with the Hastewire API through Jentic?
Search Jentic by intent such as 'humanize AI-generated text', and Jentic returns the Hastewire humanize operation with its input schema so the agent sends the right text. To run it on your own infrastructure, install Jentic One from its GitHub repo with `curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh`, then add Hastewire from the directory.
For Agents
Humanize AI-generated text, detect how AI-written a passage is, and read the account and its billed usage.
Use for: Humanize this AI-generated draft so it reads naturally, Check whether a passage looks AI-written, Retrieve the account tied to my API key, Monitor how many credits my account has used
Not supported: Does not handle translation, grammar correction, or generating text from a prompt. Use for humanizing AI text and detecting AI-written content only.
The Hastewire API rewrites AI-generated text to read more naturally and scores text for how AI-written it looks. An agent sends a block of text to the humanize operation and gets a reworked version back, or sends text to the detect operation for an AI-likelihood assessment. It also exposes the account behind the API key, billed usage, and a service status check, so an agent can track consumption and confirm the service is up before a batch.
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
Base layer of spec validity and structural soundness.
Aggregated quality score from linter diagnostics, weighted by severity.
Percentage of `$ref` references that resolve successfully.
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
Structural correctness score based on schema issues using logarithmic dampening.
Clarity, completeness, and ingestion readiness for developers and tooling.
How richly the API is illustrated with examples.
Percentage of examples that conform to their schemas.
Percentage of operations with complete response definitions (success, client error, server error).
Health of API ingestion, bundling, and resolution within Jentic pipelines.
Semantic breadth, depth, and agent comprehension for AI systems.
Coverage of descriptions across API elements.
Coverage of RFC 9457 Problem Details for error responses.
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
Coverage of summaries across operations/tags/info.
Functional utility, complexity comfort, and AI orchestration readiness.
Agent comfort level based on API operational and structural complexity.
Trust, risk posture, and security compliance.
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
Findability, semantic richness, and reasoning readiness.
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>