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roman-zaglauer

OctoBot MCP Server

by roman-zaglauer
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Python
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list_evaluators

List all OctoBot evaluators with their activation state and category. Use this to identify exact evaluator names needed before adjusting configuration.

Instructions

List every evaluator OctoBot knows about, including its activation state and category.

Tier-B (ADR-0009, reversed to GO by explicit user decision -- see this module's docstring for the full verified DOM shape and fail-loud assumptions). Closes update_evaluator_config's own companion-read gap: that tool is unusable without already knowing an evaluator's exact class name and current state. Idempotent, read-only, not confirm-gated (ADR-0003).

Output: {"evaluators": [{"name": str, "enabled": bool, "type": str}]}. name is the config-key attribute value -- the same string update_evaluator_config's patch keys must equal, making the closed loop between these two tools a structural guarantee, not a convention to maintain by hand. type is one of "technical_analysis"/"social"/ "realtime"/"scripted", taken from whichever category container an evaluator's row was found inside.

Raises EvaluatorScrapeContractBrokenError (NFR-18) only if zero evaluators are found across ALL FOUR category containers combined, or an expected container is missing from the page entirely -- never for a single category legitimately having zero evaluators (confirmed live: this project's own test instance has zero "Scripted evaluators" installed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it is exceptional: it discloses read-only/idempotent behavior, fail-loud assumptions, and precisely when EvaluatorScrapeContractBrokenError is raised versus when it is not. It even documents a confirmed live edge case to prevent false alarms.

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?

The description is longer than average but every section earns its place: core purpose is front-loaded, then usage relationship, output format, and error behavior. It is slightly dense with ADR references and governance details, but these are substantive context rather than filler.

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?

Despite having no output schema, the description fully specifies the return shape, field types, enum values, and the meaning of the name field. It also covers error semantics and lists the exact failure conditions, making the tool self-contained for an agent to invoke correctly.

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?

The tool has zero parameters, so the schema already fully covers parameter semantics and there is nothing for the description to add. The description instead clarifies the output fields and their meanings, which is the relevant semantic content for this no-argument tool.

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 opening line states a specific verb ('List'), a clear resource ('every evaluator OctoBot knows about'), and the key distinguishing details: activation state and category. It also explicitly names sibling update_evaluator_config and explains how this tool closes its read gap, so an agent can tell them apart.

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?

The description gives explicit usage context: this is the companion-read for update_evaluator_config, which is unusable without knowing an evaluator's exact class name and current state. It also states that the tool is idempotent, read-only, and not confirm-gated, giving clear behavioral guidance for when it is safe to call.

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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