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agenttune

by com.agent-tune

Get a tuning file (paste-ready Markdown)

get_tuning
Read-only

Fetch one tuning file as Markdown with YAML front-matter. The front-matter is machine-readable install metadata (install.surfaces = where to write it per agent surface, verify.probe = how to confirm it took effect); the body is the behavioral tuning to load as system-prompt content. MIT licensed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesType slug, lowercase. mbti: 4-letter code (intj). enneagram: N-name (5-investigator). disc: letter-name (d-dominance). attachment: style (secure). ocean: dimension-pole (openness-high). Unsure? Call list_tunings.
systemYesPersonality system.

TDQS

A3.9/5.0
Behavior4/5

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

The description explains the return format (Markdown with YAML front-matter) and outlines the front-matter structure (install.surfaces, verify.probe, MIT license), adding context beyond the readOnlyHint annotation.

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 main description is two concise sentences that front-load the key purpose and output format. Extra detail in the slug description is appropriate within the schema.

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 no output schema, the description adequately explains the return structure and content, covering the front-matter and body. Lacks discussion of error cases but sufficient for a read-only fetch.

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?

Schema coverage is 100%, so the description adds minimal extra meaning. The slug field example and cross-reference provide slight guidance, but no significant semantic additions.

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 title and description clearly state the tool fetches one tuning file as Markdown with YAML front-matter, distinguishing it from sibling tools like list_tunings and get_test_spec.

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 usage through the slug field's cross-reference to list_tunings, but does not explicitly state when to use this tool versus alternatives.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: retrieving a test specification, listing available tunings, and fetching a specific tuning file. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent 'verb_noun' pattern using snake_case (get_test_spec, get_tuning, list_tunings), making them predictable and easy to understand.

Tool Count5/5

With 3 tools, the server is tightly scoped to its personality tuning domain. Each tool serves a necessary function without redundancy or excess.

Completeness5/5

The tools cover the complete workflow: retrieve a test spec, list tunings to find the matching slug, and fetch the tuning file. The description includes clear instructions for scoring and installation, leaving no gaps.

Resources