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mo9652962-ai

skill-maintenance-mcp

by mo9652962-ai

Skill Read Decisions

skill_read_decisions

Read a skill's decision-log entry titles before revising it to avoid repeating past mistakes.

Instructions

读取技能 decision-log 概要(条目标题列表),修订前先看避免重复踩坑。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses the return shape (a summary of titles rather than full entries), but says nothing about permissions, scope of the log, or size limits. It is a safe read, which limits risk, but disclosure is thin.

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?

A single compact sentence, front-loaded with the action and resource, with the usage rationale appended. No wasted words, though the terseness contributes to the gaps noted elsewhere.

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?

An output schema exists, so return values need not be described, and this is a simple read tool. Still, the one required parameter's expected value is never addressed, which leaves the definition under-complete for correct invocation.

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 description coverage is 0% and the description never explains what skill_path should contain (a directory? a skill identifier? a file path?). With one undocumented required parameter and no compensating text, an agent must guess the expected format.

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: reading the skill decision-log summary, and clarifies the granularity (entry title list). It is distinguishable from the sibling skill_log_decision (which writes) by the read/revise framing, though it never names siblings explicitly.

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?

Gives an implied usage condition — review before revising to avoid repeating past mistakes — which is useful context. However, it does not name alternatives (e.g., skill_log_decision for writing) or state when not to use it, leaving routing to inference.

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