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tengolabs

killbottleneck-mcp

Official

list_rule_runs

Monitor automation rule execution on a map by reading the run log, showing which rules fired, on which nodes, and the outcome (ok, failed, skipped with safety stop reason).

Instructions

Read the run log of a map's automation rules (newest first, max 100): what fired, on which node, ok/failed/skipped and what the actions did. skipped = a safety stop (rule chain depth or per-save cap), detail says which.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
map_idYes
rule_idNoOptional: only runs of this rule

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.33.2-beta

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates a read operation ('Read'), defines output semantics (ok/failed/skipped), and explains the non-obvious 'skipped' status as a safety stop with a detail field. This goes beyond minimal transparency, though it does not mention potential edge cases like empty results or rate limits.

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, front-loaded with the action ('Read the run log'), and each phrase provides useful information: ordering, limit, output fields, and status explanation. No filler or redundancy.

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?

Given there is no output schema, the description adequately explains what the tool returns: recent run logs with node, status, action outcomes, and special handling of 'skipped'. It covers the essential behavior for a read-only log tool, though it could mention the response format (e.g., array) or pagination limits beyond 'max 100'. Overall, it is reasonably complete for the tool's complexity.

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?

The input schema documents 'rule_id' as optional and its purpose ('only runs of this rule'), covering 50% of parameter semantics. The description adds contextual meaning by referring to 'a map's automation rules', helping to clarify that 'map_id' is the map identifier. However, it does not explicitly name the parameters or add detail beyond the schema for 'map_id', making it adequate but not exceptional.

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?

The description starts with 'Read the run log of a map's automation rules', which uses a specific verb ('Read') and resource ('run log'), making the tool's purpose unambiguous. It also specifies key details like ordering (newest first), limit (max 100), and output fields (node, ok/failed/skipped, actions), clearly distinguishing it from sibling tools like list_rules.

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 implies when to use it (when you need to inspect rule run history), but it does not explicitly state when not to use it or name alternatives. For example, it does not contrast with list_rules or explain that this is for execution history rather than rule definitions. The context is clear but lacks explicit exclusion guidance.

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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