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Human For AI

Message the human operator

message_human_operator

Send a free-form message to the human operator — questions, scoping, custom or recurring projects, anything that is not yet a ready-made task. reply_to is REQUIRED: an email a human can read (MX-checked), or an https URL to receive the reply as a signed webhook push. The response also carries thread_url + access_token — every message is a pollable thread, so you can read the reply with check_message_thread even without a mailbox. Keep the token: it is shown only once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromNoYour agent or system identifier
messageYesThe message. Plain language, English.
subjectNoShort subject line
reply_toYesREQUIRED. Email address for the reply (real, reachable, MX-checked) — or an https webhook URL for a signed push.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already flag a non-read-only, non-idempotent, open-world operation, so the description carries the burden of richer context — and it delivers substantially: the MX-checked email/https webhook reply mechanism, the pollable-thread model (thread_url + access_token), and the security-critical disclosure that the token 'is shown only once.' This is exactly the kind of behavioral and operational context annotations cannot convey.

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?

Three dense sentences, each earning its place: purpose and scope first, then the reply_to requirement with its two delivery mechanisms, then the thread/token return behavior with the one-time-display warning. No padding, no filler, and the most operationally critical detail (token shown only once) is placed in the final sentence without being buried.

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?

With no output schema, the description carries the burden of explaining return values — and it does: the response carries thread_url + access_token, every message is a pollable thread, and check_message_thread is named as the follow-up path even without a mailbox. For a flat 4-parameter message-sending tool, nothing an agent needs to call it correctly and retrieve the reply is missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds genuine meaning beyond the schema by specifying what belongs in message (questions, scoping, custom/recurring projects) and by explaining why reply_to is the delivery path for the reply. It does repeat some reply_to details that the schema already covers nearly verbatim, but the message-content guidance is a real addition above baseline.

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?

States a specific verb+resource pair ('Send a free-form message to the human operator') and immediately scopes it with 'anything that is not yet a ready-made task,' which cleanly separates it from siblings like submit_human_task. The free-form versus ready-made distinction is precise and actionable, so an agent knows exactly what this tool is for without opening other schemas.

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 explicit when-to-use context ('questions, scoping, custom or recurring projects') and names check_message_thread as the companion tool for reading replies. However, the primary alternative for ready-made tasks (submit_human_task) is never named; the exclusion is implied by 'not yet a ready-made task' rather than stated as an explicit when-not-to-use rule, which keeps it just shy of a 5.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: discovery, structured task submission/status, free-form messaging, and threaded replies. Potential overlaps like submit vs. message vs. reply are clearly separated by input requirements and response types.

Naming Consistency4/5

All names are snake_case and action-first, which makes them predictable as a set. The only minor deviation is 'reply_in_message_thread' including a preposition, but it remains clear and consistent in style.

Tool Count5/5

Six tools is well-scoped for the service: one discovery tool, two task lifecycle tools, and three messaging/thread tools. There is no redundant surface area.

Completeness4/5

The core lifecycle is covered: discover, submit, poll, receive verification, and exchange follow-up messages. The main gap is the lack of an explicit cancel or amend task operation, though agents can work around it by messaging the operator.