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BTCDecoded Intelligence

assess_argument

Read-onlyIdempotent

Match the claim to a discourse game, then the documented counter-move, from Bitcoin_Discourse_Games or Bitcoin_Governance_Complete_Argument_Map. Return pattern + cites. No new synthesis. These files are product policy (internal), not contemporaneous evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesClaim or thread excerpt to match against the documented discourse games.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the tool is non-destructive and open-world. The description adds that no new synthesis occurs and the files are product policy, not contemporaneous evidence. It doesn't contradict annotations; it complements them by clarifying the nature of the data. The description adds valuable context about the tool's internal behavior, which is more than just repeating annotations.

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?

The description is concise and front-loaded with the main action ('Match the claim to a discourse game') and the resources. It provides critical constraints (no new synthesis, internal files) in a compact way. No wasted words, structured effectively for quick consumption.

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

Completeness3/5

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

Given the tool has a single string parameter and no output schema, the description covers the purpose and key constraints. It doesn't describe the return format beyond 'pattern + cites', which might be sufficient for an agent. However, it could clarify what is meant by 'pattern' and 'cites' or how the output is structured, but given the simplicity, it is adequate.

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 100%, so the parameter 'text' is already well-documented in the schema. The description adds that 'text' should be a claim or thread excerpt to match, which does not go beyond the schema's description. Since coverage is high, a baseline of 3 is appropriate; the description adds no extra semantic detail.

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?

The description clearly states that the tool matches a claim to a discourse game and returns pattern and citations. It identifies the specific resources used (Bitcoin_Discourse_Games or Bitcoin_Governance_Complete_Argument_Map). It does not explicitly differentiate from siblings, but the verb 'assess' and focus on argument patterns distinguishes it from more general tools like search or analyze_pr.

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?

The description implies usage: when you need to classify a claim into a discourse game and find documented counter-moves. It provides implicit guidance by noting what it does not do ('No new synthesis') and the context of the files. It doesn't explicitly name alternatives, but the sibling list suggests other tools are for different purposes (e.g., analyze_pr for PRs, find_precedent for precedents).

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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