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Inarus

provgraf-mcp

by Inarus

precedents

Find semantically closest earlier rulings and open structural questions before resolving a new dilemma. Reuse existing rationales instead of starting from scratch.

Instructions

Decision precedents: the semantically closest EARLIER rulings (decision) and open structural questions. Run this BEFORE settling a new dilemma — if a similar one was already settled, reuse that rationale instead of asking from scratch.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
queryYes
clientNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the semantic closeness behavior and the dual output (decisions and open questions), but does not mention potential side effects, rate limits, or what happens when no precedents exist. Adequate for a read-only tool, but not comprehensive.

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?

The description is two sentences, extremely concise, and front-loads the core purpose before usage guidance. No unnecessary words, and it reads naturally.

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

Completeness2/5

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

The description explains the tool's purpose and when to use it, but omits parameter semantics and the output format. Given no output schema, the agent is left without enough context to correctly invoke the tool with appropriate parameters or interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides zero explanation of the query, k, or client parameters. Schema coverage is 0%, so the agent has to infer from parameter names alone. This is a critical gap for a tool with 3 parameters, especially since query is required.

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 the tool returns semantically closest earlier rulings and open structural questions, and frames it as a lookup for prior decisions. It distinguishes from siblings implicitly by focusing on precedent reuse, though it doesn't explicitly name alternatives.

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 explicitly instructs to run this before settling a new dilemma and to reuse the rationale if a similar one exists. This gives clear contextual guidance, though it doesn't explicitly mention when not to use or name sibling alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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