Kellian

Withdraw a market's current research as the approved producer that published it

kellian_withdraw_research

Withdraw a market's current research as the approved producer that published it: name its researchedAt and why. Readers then see no research; the venue keeps the record. To fix research instead, publish it with correctionReason.

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": {
      "address": "<address>",
      "chainId": "<chainId>",
      "researchedAt": "<researchedAt>",
      "reason": "<reason>",
      "idempotencyKey": "<idempotencyKey>"
    },
    "name": "kellian_withdraw_research"
  }
}

Input Schema

Name	Required	Description
`reason`	Yes	Why it is withdrawn, shown to readers after "Withdrawn because": one clause, e.g. "it misread the market's rule".
`address`	Yes	Checksummed or lowercase 20-byte EVM address (0x + 40 hex).
`chainId`	Yes
`researchedAt`	Yes	The researchedAt of the market's current research, the research withdrawn: a newer version is never withdrawn by mistake.
`idempotencyKey`	Yes	Stable retry key. Reuse only with byte-equivalent tool arguments.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 5, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Beyond the annotations, it discloses the concrete effect ('Readers then see no research; the venue keeps the record'), which confirms a soft, record-preserving withdrawal consistent with destructiveHint=false. What it does not cover is authorization failure behavior or the tension between a required idempotencyKey and idempotentHint=false, which the description leaves silent.

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?

Three short sentences with the operation and required inputs front-loaded, then the reader-facing effect, then the corrective alternative. Every sentence carries distinct information and nothing is padded.

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?

With a required 5-parameter mutation, an output schema, and covering annotations, the description supplies the role requirement, version targeting, and visible effect needed to call it correctly. Only error and recovery behavior (e.g., when the caller is not the approved producer) is unspecified.

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 80%, so the schema already explains reason (reader-visible text) and researchedAt (version targeting). The description's 'name its researchedAt and why' largely restates those semantics rather than adding new meaning; no syntax, format, or edge-case guidance is added.

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?

The description states a specific verb ('Withdraw') and resource ('a market's current research') plus the required actor role ('as the approved producer that published it'). This clearly distinguishes it from kellian_publish_research and kellian_get_market_research in the sibling list.

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?

It gives an explicit when-not-to-use route: 'To fix research instead, publish it with correctionReason.' The agent is told the alternative tool and the exact parameter that selects that path, so no inference is required.

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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