Skip to main content
Glama

Re-humanize a job's still-flagged passages for free

free_rehumanize

Continue a completed humanizing job at no cost by uploading a fresh AI-detection report; only passages still flagged are rewritten.

Instructions

Continue a finished humanize job for FREE. Upload a fresh detection report for that job's result; only the passages it still flags are rewritten, at no credit cost. The server enforces strict limits: one free continuation per job, a per-day cap, the report must be of THAT job's own result (>=90% match) and show >=20% AI, and the result must still exist (kept ~7 days). If a limit is not met it returns a clear reason - relay it and stop; do not retry or silently fall back to a paid job. Pass the job_id a prior humanize_document (or check_job) returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe finished humanize job to continue (its job_id from humanize_document/check_job)
segmentsNoPer-passage word control for the still-flagged passages (optional), same shape and experimental caveat as humanize_document.segments
output_pathNoWhere to write the result; defaults to beside the report
report_pathYesAbsolute path to the fresh Turnitin/iThenticate report for that job's result
instructionsNoExtra requirements for this job
wait_secondsNoHow long to wait before returning a job id (default 55)
Behavior5/5

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

With no annotations provided, the description fully discloses server-side constraints: one free continuation per job, per-day cap, required >=90% match, >=20% AI in the report, and that results are kept ~7 days. It also explains error handling and prohibits retries/fallback, making behavior highly transparent.

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 moderately lengthy but every sentence contributes essential information (free nature, limits, error behavior, no-fallback rule). It is front-loaded with the core purpose, making it easy to parse despite the detail.

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?

Given 6 parameters, no annotations, and no output schema, the description covers the tool's core behavior, constraints, and error handling well. It omits explicit return-value information, but since no output schema exists, this is not strictly required. It is adequately complete for the tool's complexity.

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 coverage is 100% for all six parameters, so the baseline is 3. The description adds minimal semantic value beyond the schema; it mentions passing job_id from a prior humanize_document/check_job, but the schema already states this. Optional parameters are not elaborated in the description, though the schema covers them.

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 explicitly states the tool continues a finished humanize job for free, rewrites only still-flagged passages, and is distinct from the paid sibling humanize_document. It also includes the directive not to fall back to a paid job, which further distinguishes it from alternatives.

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?

Provides clear context: use after a finished humanize job with a fresh detection report. It includes when-not-to (do not retry or silently fall back to a paid job) but does not explicitly name alternative tools like check_job for status checks, so it stops short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/humanpen/humanpen-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server