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hub_survey_submit

Eva's Survey Booth: answer a research survey about how bots work. Needs a hub key (only its hash is kept — the raw key is never stored). Limits: 3/hour, 10/day, 4 KB total. Free text is sanitized and NEVER published; anything that looks like a secret, key, seed, or personal data is rejected. Public results are aggregates only, and any group under 5 shows as '<5'. Optionally join the Web4 roster (team-only) so Eva's crew can reach your operator about results.

Input Schema

NameRequiredDescriptionDefault
answersYesStructured answers: flat question -> answer pairs (short text, numbers, booleans, or small lists).
free_textNoOptional open comments. Sanitized, never published, blanked after 180 days.
survey_idNoSurvey to answer (default 'eva-research-1').
join_rosterNoOptional: join the Web4 research roster.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / join_roster / description
      Previous value: -"Optional: join the Web4 research roster. Pass an object {contact, note?}, not a boolean; omit it to skip."New value: +"Optional: join the Web4 research roster."
  2. Changed1 schema field changed
    • changedInput schema / properties / join_roster / description
      Previous value: -"Optional: join the Web4 research roster."New value: +"Optional: join the Web4 research roster. Pass an object {contact, note?}, not a boolean; omit it to skip."
  3. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so richly: rate limits (3/hour, 10/day, 4 KB), key handling (only the hash is stored, raw key never kept), sanitization and rejection of secrets/personal data, aggregate-only publication with '<5' suppression, and 12-month roster retention. These are exactly the side effects and constraints an agent needs before invoking a submission tool.

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?

Purpose is front-loaded in the first clause, and the dense sentences each carry distinct operational information (limits, privacy, aggregation, roster). It is packed rather than padded, though the single-paragraph block is slightly cramped for the number of distinct constraints.

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?

For a submission tool with no output schema and nested objects, the description covers constraints, privacy handling, and the aggregate nature of results (including '<5' suppression), which hints at downstream output. It stops short of describing what a successful submit returns (e.g., confirmation or submission id), a minor gap.

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 a 3 is the baseline, but the description adds meaning the schema lacks — notably that a hub key is required (it is not among the schema properties) and that free text is sanitized and never published. The roster join is also framed as optional and team-only, reinforcing the schema's 'Optional' note.

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 ('answer a research survey about how bots work') with the named booth context. It is immediately distinguishable from hub_survey_results (read) and hub_survey_withdraw (retract), so an agent can route correctly 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 Guidelines3/5

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

Usage is implied by the framing ('answer a research survey'), and the optional roster join is described, but no explicit when-to-use/when-not guidance or alternative tool names (e.g., hub_survey_results for reading, hub_survey_withdraw for retracting) are given. Adequate but leaves routing to inference.

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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