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AgentMart

by ai.ciphyr.agentmart
OverviewDiscussionsAdmin

Ask my human a question by email

ask_human

Ask your human owner a question by email (needs an ask-my-human utility from buy). Give 2 to 6 short options for one-tap answers, or free_text: true for a written answer. Plain words about a decision only: no links, instructions, secrets, phone numbers or company framing. Returns ask_id: poll get_ask, or pass inbox_instance_id to get the answer in your webhook inbox. Pass idempotency_key so a retry returns the same ask and never emails twice. Your owner confirms on a page, so an answer can take hours.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optionsNo2 to 6 distinct labels, up to 60 characters each.
questionYesUp to 500 characters of plain words.
free_textNotrue: your owner writes the answer. Do not send options then.
instance_idYesUtility instance id from buy or list_utilities.
passport_tokenNoYour amp_ token, only if your client cannot send it as an Authorization header; leave it out when your MCP app signed in.
idempotency_keyNoYour own id for this question: a retry with the same key returns the same ask.
expires_in_hoursNo1 to 168, default 72.
inbox_instance_idNoOne of your webhook inboxes: the answer is also delivered there.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • changedInput schema / properties / passport_token / description
      Previous value: -"Leave it out when your MCP app signed in to AgentMart (it is refused then). Otherwise your passport bearer token (amp_...) or session token (amp_s_...), only if your client cannot send it as an Authorization header. A token here sits in your context, so it never authorizes sensitive actions."New value: +"Your amp_ token, only if your client cannot send it as an Authorization header; leave it out when your MCP app signed in."
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Adds substantial context beyond annotations: the email may double-send without idempotency_key, the owner confirms on a page so answers can take hours, and the result is an ask_id to be polled. This is exactly the operational knowledge (retry safety, latency, side effect) that readOnlyHint=false and openWorldHint=true 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?

Every sentence carries unique information: creation semantics, content rules, response shape, idempotency, and latency. The most actionable facts (returns ask_id, retry safety) are front-loaded and nothing is padded.

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?

For an 8-parameter mutation tool with no output schema, the description covers the return value (ask_id), the follow-up mechanism (get_ask / webhook inbox), retry behavior, and expected latency. Nothing an agent needs to call it correctly is missing.

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%, so the schema already documents every parameter including options, free_text, idempotency_key and inbox_instance_id. The description reinforces the options/free_text trade-off but adds little syntax or meaning beyond what the schema states, matching the baseline 3.

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 and resource ('Ask your human owner a question by email') and immediately distinguishes itself from the related siblings get_ask (poll) and delete_ask (cleanup) by naming get_ask as the polling counterpart. An agent can identify this as the ask-creation tool without opening the schema.

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?

Gives a clear prerequisite ('needs an ask-my-human utility from buy'), content constraints (plain words, no links/instructions/secrets), and names the alternative consumption paths (poll get_ask or route to a webhook inbox). It stops short of contrasting with other communication siblings like send_feedback, but the when-to-use context is solid.

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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