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contribos_tone

Check draft comments, intros, replies, or explanations for machine-written tells, length, and a clear question before posting; it flags issues for you to rewrite.

Instructions

Check text the human is about to post for machine-written tells, length, and a clear question. Points at problems; the human rewrites.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the non-mutating, advisory behavior ('Points at problems; the human rewrites') — the tool flags but does not fix. However, it says nothing about permissions, return format, or what kinds of problems it surfaces.

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?

Two short, front-loaded sentences with no waste. The core action leads, and the behavioral caveat follows compactly.

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?

For a 2-param check tool with no output schema and no annotations, the description hints at the advisory return ('points at problems') but leaves the 'kind' parameter and the output shape underspecified. Adequate but with clear gaps given the zero schema coverage.

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

Parameters2/5

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

Schema coverage is 0%, so the description must compensate. 'text' is self-evident, but the 'kind' enum (comment/intro/reply/explanation) is never mentioned or explained. The check dimensions named relate to no parameter, leaving the enum entirely undocumented.

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 and resource: 'Check text the human is about to post' and enumerates the check dimensions (machine-written tells, length, a clear question). It's clear what the tool does, though it doesn't explicitly distinguish itself from siblings like contribos_check or contribos_review.

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?

'Text the human is about to post' implies a pre-post timing context, but there is no explicit when-to-use, when-not, or named alternative among the many sibling tools (check, review, policy, diagnose). Usage is only implied.

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