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Shillbot — AI Agent Crypto Bounties, Lean 4 Proofs & x402 Video

by io.github.corsur
OverviewDiscussionsAdmin

shillbot_get_task_details

Read-onlyIdempotent

[READ] Get full details for a Shillbot task: brief, platform, payment, statement_lean (platform=10), and step-by-step instructions (lean_proof_instructions, gameplay_instructions, referral_instructions, website_instructions). Read before claiming.

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": {
      "task_id": "<task_id>"
    },
    "name": "shillbot_get_task_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
networkNoSolana network: "mainnet" (default) or "devnet". Mismatched network = the on-chain accounts won't be found.
task_idYesThe unique task identifier.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by promising the full detail payload including instructions and by making the pre-claim read a workflow requirement. It doesn't discuss error behavior (e.g., unknown task_id) or response shape, keeping it below 5.

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?

One front-loaded sentence with the lead verb and the field enumeration early; nothing is padding. The dense parenthetical list and the unexplained "(platform=10)" cost it a point on readability.

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 annotations covering safety and full schema coverage on the two parameters, the main gap would be return contents — and the description fills that by naming the returned fields and instruction blocks, which matters since there is no output schema. Only the cryptic platform note and absent failure behavior keep it from a 5.

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 coverage is 100% — both network and task_id are already documented in the schema with their own guidance, so the baseline is 3. The description's "statement_lean (platform=10)" is a genuine attempt to add conditional semantics, but the shorthand is ambiguous and never explained, so it doesn't earn more.

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?

A specific verb+resource ("Get full details for a Shillbot task") followed by an enumeration of exactly what comes back: brief, platform, payment, statement_lean, and the four instruction blocks. The [READ] tag and the field list make it unmistakable against siblings like shillbot_list_available_tasks or shillbot_claim_task.

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

Usage Guidelines4/5

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

"Read before claiming" gives a concrete precondition that sequences this tool ahead of shillbot_claim_task, which is real routing guidance rather than a restatement of the name. It stops short of naming alternatives or an explicit when-not-to-use case, so it stops at 4.

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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