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Record the user's explicit acceptance of a HumanFn offer

accept_human_function_offer
Idempotent

Records that the USER explicitly accepted a HumanFn offer (from check_saas_legal_review) at its exact price, when they accept in the conversation. Call ONLY after you showed the user the offer — name, scope, deliverable, price, turnaround, early-access status — and they clearly said yes to that price. Pass their words verbatim as user_confirmation. Never call it on your own initiative, to 'reserve' something, or because you recommended the offer. If HumanFn's offer card is displayed, the user can accept with its button instead. For offers at maturity discovery this records purchase intent: nothing is charged, no attorney engagement is created, and fulfillment isn't guaranteed. The result includes a message for the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offer_idYesThe offer ID returned by check_saas_legal_review (off_…).
contact_emailNoOptional. Only with the user's permission: lets HumanFn contact them if it can arrange the service.
user_confirmationYesThe user's own words accepting the offer, verbatim (e.g. 'Yes, I accept the review at $499').
accepted_price_usdYesThe exact price the user accepted, as shown in the offer (e.g. 499). Must match the offer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / offer_id / description
      Added value: +"The offer ID returned by check_saas_legal_review (off_…)."
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations declare the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=true), and the description adds substantive consequences beyond them: at maturity discovery nothing is charged, no attorney engagement is created, fulfillment isn't guaranteed, and a user-facing message is returned. That is exactly the kind of side-effect disclosure annotations cannot carry.

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?

Front-loads the core action and the hard precondition before the negative constraints, and every sentence carries a rule. Slightly long and a few clauses restate the schema's verbatim/price requirements, but there is little true waste for a high-risk consent-recording tool.

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 a non-idempotent-looking write that records user consent, the description covers trigger conditions, anti-patterns, the alternate UI path, the financial/legal meaning at maturity discovery, and that the result contains a user message. No output schema exists, so nothing else is required.

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 defines offer_id format, accepted_price_usd matching the offer, and verbatim user_confirmation. The description only reinforces ('Pass their words verbatim', 'at its exact price') without adding new syntax or constraints, so the baseline 3 applies.

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?

Specific verb ('Records') + resource ('USER's explicit acceptance of a HumanFn offer') with the offering sibling named (check_saas_legal_review). An agent can distinguish this from confirm_execution or offer_card_event without opening a schema.

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?

Explicit preconditions ('Call ONLY after you showed the user the offer — name, scope, deliverable, price, turnaround, early-access status — and they clearly said yes') plus explicit exclusions ('Never call it on your own initiative, to reserve, or because you recommended it') and the alternative path (offer card button).

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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