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b612 (hakuto AI)

b612 レビュー観点(対象別)

b612_review_checklist

対象の種類に応じた b612 のレビュー観点を返す。返ってきた観点を使って呼び出し側の AI が実レビューを行う。対応: lp, hp, ec, api, saas, game, form, generic

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_typeYesレビュー対象の種類。次のいずれか: lp, hp, ec, api, saas, game, form, generic(不明なら generic)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It does disclose the division of labor (this returns data; the caller does the reviewing), which usefully implies a read-only lookup, but it says nothing about error behavior for an unsupported type or the shape/size of the returned checklist.

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?

Three short sentences, front-loaded with the core action and ending with the supported values. No filler, though the trailing value list duplicates the schema enum.

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 single-parameter lookup with no output schema, the description covers what is returned, who consumes it, and the accepted inputs. Only the omission of the return structure and unsupported-type handling keeps it from being fully complete.

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% and the schema already lists the accepted target_type values with a fallback to generic. The description repeats that same list rather than adding syntax, format, or fallback semantics beyond what the schema provides, so baseline 3 applies.

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+resource: returns b612 review perspectives keyed by target type, and explicitly says the caller's AI uses them to run the actual review. It doesn't differentiate itself from similar-sounding siblings like b612_principles or b612_rules, which an agent could confuse with a checklist feed.

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?

The description gives implied usage context — pass a target type, get perspectives, then perform the review yourself. But it names no alternatives and gives no when-not guidance against the other b612_* retrieval tools.

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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