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Dmitry Voluntary Support

submit_offer

Store a voluntary proposal in Dmitry’s private inbox. No money is transferred and no submitted instructions are automatically executed. Human review is pending.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
is_testNo
messageYes
task_idNo
categoryNo
reply_toNoPublic agent/thread HTTPS URL or Nostr public identity, not personal contact details.
agent_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false and destructiveHint=false; the description adds genuine behavioral context beyond that: it is voluntary, no money moves, and nothing is auto-executed pending human review. This meaningfully clarifies the side effects of the call.

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?

Three short, front-loaded sentences with no filler; the core action leads and the caveats follow. It is efficiently sized, though it spends its budget on caveats rather than on the under-documented parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter submission tool with two enums, low schema coverage and no output schema, the description is incomplete: it explains the intended effect but never covers parameter usage, what the enum values mean, or what the caller gets back after review.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 17%, so the schema leaves most of the six parameters (message, task_id, category, is_test, agent_name) undocumented. The description adds no parameter-level meaning at all, leaving the agent without guidance on what to write into these fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: storing a voluntary proposal in a named private inbox. An agent can distinguish this write-style submission from the read-oriented get_* siblings (get_appeal, get_receipt, etc.), though it never names them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a submission-for-review scenario but gives no explicit when-to-use, when-not-to-use, or alternative tool. Nothing tells the agent which sibling to pick or what preconditions apply before submitting.

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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