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pending_changes

Read-only

Preview staged firewall rules before applying to detect lockout risks that could cut management access; reports worst-first findings and blocks unsafe commits.

Instructions

[READ] The staged rule set apply_changes would commit, with lockout risk.

Run this BEFORE apply_changes. It reports whether committing the staged rules would cut the endpoint this tool manages the firewall through — a disabled 'pass' rule that permits management access, or an enabled 'block' rule that covers it. Findings are ranked worst-first and carry a certain flag: certain ones make apply_changes refuse, uncertain ones (alias destinations, 'any', interface groups) are warnings only and never block.

basis states what this is: the staged rule STATE, not a diff against the running config — neither platform exposes a per-rule dirty flag over REST.

Args: target: Firewall target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only grant readOnlyHint=true, but the description adds substantial behavior: what constitutes lockout risk (disabled pass rule / enabled block rule over the management path), worst-first ranking, the `certain` flag semantics, and what blocks vs warns. It also clarifies that `basis` reports staged STATE, not a diff — a non-obvious behavioral detail no structured field carries.

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?

Front-loads the [READ] tag, then usage, then behavioral detail, then args — a sensible ordering. Every section adds information, though the prose is denser than strictly necessary; the `basis` paragraph earns its place by preventing a state/diff misread.

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

Completeness5/5

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

With no output schema and a single optional param, the description still describes what is returned (ranked findings, certain flag, basis semantics) and the gating relationship to apply_changes. Nothing needed to call it correctly is missing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the param, and it does: 'target: Firewall target name from config; omit for the default.' This explains both the meaning and default behavior. It stops short of format examples, but for a single optional string it is adequate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: it reads the staged rule set that apply_changes would commit, specifically surfacing lockout risk. It is clearly distinguished from apply_changes (which commits) and from state-inspection siblings, and the [READ] tag disambiguates intent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit routing: 'Run this BEFORE apply_changes,' which directly names the sibling it gates. It also describes the consequence of each finding class (certain ones make apply_changes refuse, uncertain ones warn only), giving the agent a clear decision model for when this tool matters.

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