perfect-world

evidence_pack_submit

FREE: submit one question to the Evidence Pack desk. Never charges. A person reviews it and answers with an acceptance, a narrower scope, or a quote.

    question: the ONE thing you want established. subject: the project or issue.
    jurisdiction: the city/county/state. reply_to: an email a person can answer.
    sources: optional URLs or citations you already have.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "question": "<question>",
      "subject": "<subject>",
      "jurisdiction": "<jurisdiction>",
      "reply_to": "<reply_to>"
    },
    "name": "evidence_pack_submit"
  }
}

Input Schema

Name	Required	Description	Default
`sources`	No
`subject`	Yes
`question`	Yes
`reply_to`	Yes
`jurisdiction`	Yes
`source_pages`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 6, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses cost (free), human mediation ('A person reviews it'), and possible outcomes (acceptance, narrower scope, quote). It does not mention latency or asynchronous behavior, but core behavioral traits are transparent.

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?

Compact and front-loaded with the most decision-relevant facts (FREE, human review, outcome types). The parameter lines are scannable with no redundant prose.

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?

Given no output schema and no annotations, the description covers the workflow, the required fields, and the optional sources field. The only notable omission is source_pages; overall an agent has enough to call the tool correctly.

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 0%, but the description provides meaningful glosses for question, subject, jurisdiction, reply_to, and sources. source_pages is left unexplained, which is a minor gap given it is optional and has a default.

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 (submit) and resource (one question to the Evidence Pack desk), and clarifies it is a free, human-reviewed request. It is clearly distinguishable from general-purpose tools, though it does not explicitly contrast with the sibling evidence_pack_offer.

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?

Implied by 'submit one question to the Evidence Pack desk': this is for requesting a human research/evidence determination. It does not explicitly state when to prefer it over evidence_pack_offer or other siblings, and there are no exclusions or prerequisites. This is adequate but not explicit routing.

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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