Deterministic Music Theory for Claude, Cursor, and Autonomous AI Agents
Large Language Models (LLMs) frequently hallucinate music theory, leading to incorrect notes, false Roman numerals, and broken voice leading. THIRI solves this by providing a deterministic, mathematical music-theory engine (pitch-class-set theory over ℤ/12) directly to your AI.
It gives AI assistants precise, reproducible harmonic reasoning in milliseconds, allowing them to write correct musical scores, analyze progression
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Average 3.6/5 across 5 of 5 tools scored. Lowest: 2.7/5.
analyze_chord and resolve_chord both operate on a chord symbol and return theoretical information, which could cause confusion when agents need note frequencies vs. functional analysis. The other tools (generate_voicing, reharmonize, conduct_band) are clearly distinct in purpose.
Most tools follow the verb_noun pattern (analyze_chord, generate_voicing, resolve_chord, conduct_band). 'reharmonize' is a single verb without an object, deviating slightly from the consistent convention.
Five tools is a reasonable count for a music theory server, but 'conduct_band' feels like an outlier compared to the chord-focused tools, making the set slightly less cohesive. Each tool still has a clear role.
The server covers chord analysis, resolution, voicing, and reharmonization, covering the main chord intelligence workflows. Minor gaps exist, such as no dedicated inversion or progression generation tool, but the core surface is functional.
analyze_chordAParse a chord into root, quality, intervals, and (with a key) roman numeral + function.
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | ||
| chord | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds the output components (root, quality, intervals) but does not disclose any additional behavioral traits such as error handling, edge cases, or format constraints. It adds some value but not rich context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately states the action and outputs. It avoids redundancy and includes the key caveat about the key in a natural way. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description needs to explain return values; it does so by listing root, quality, intervals, and roman numeral + function. It also clarifies the role of the optional key. For a straightforward read-only analysis tool, this is sufficient, though it does not mention error behavior or chord notation specifics, keeping it just short of full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does explain that 'key' is used to derive roman numeral and function (implying it is optional, as the schema does not require it), but it does not describe the expected format for the chord or key strings. This adds some meaning beyond the schema but leaves significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Parse' and a clear resource 'chord', and enumerates the outputs: root, quality, intervals, and roman numeral + function. This clearly distinguishes it from sibling tools like generate_voicing or reharmonize, which imply creation or alteration rather than analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for chord analysis and mentions that a key is needed for roman numeral/function, but it does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria. It provides no direct comparison with siblings, so usage guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
conduct_bandAArrange a 4-piece band from a natural-language prompt. Returns conductor tempo/groove, 4 lanes of note events, lead sheet, and base64 MIDI. Audio render (Csound → WAV) stays on local thiri-conductor-mcp / POST /v2/render.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | ||
| durationSec | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it returns specific artifacts (tempo/groove, note lanes, lead sheet, base64 MIDI) and notes that audio rendering is deferred to an external endpoint, preventing misconceptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three purposeful sentences: purpose, output contents, and rendering behavior. Each sentence carries distinct information without redundancy or fluff, making it front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but the description lists key return values adequately. However, it omits parameter details (durationSec) and any prompt constraints, leaving users guessing on important inputs for a complex generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must document parameters. It only implicitly covers 'prompt' via 'natural-language prompt'; 'durationSec' is entirely undocumented. This is a significant gap for schema-less parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool arranges a 4-piece band from a natural-language prompt, using the specific verb 'arrange' and resource 'band.' This distinguishes it conceptually from sibling tools focused on chord analysis, voicing, reharmonization, or chord resolution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly signals use cases: when a full band arrangement from a natural-language prompt is needed. It does not explicitly name alternatives or exclusions, but the context is unambiguous compared to more granular sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_voicingCInstrument-ready voicing in a style; pass previousNotes for a voice-leading score.
| Name | Required | Description | Default |
|---|---|---|---|
| chord | Yes | ||
| style | No | ||
| octave | No | ||
| keyContext | No | ||
| previousNotes | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that previousNotes enables voice-leading scoring and that output is 'instrument-ready,' but lacks details on style handling or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with two short sentences and no wasted words. However, the first sentence is a fragment, which slightly hampers clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and minimal annotations, the description is insufficiently complete. It does not explain the return value, how style is selected, or the roles of octave and keyContext.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for all 5 parameters. It only clarifies previousNotes (voice-leading) and indirectly mentions style, leaving chord, octave, and keyContext unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a noun phrase 'Instrument-ready voicing in a style' rather than a clear verb, making the action implicit. It does not differentiate from sibling tools like analyze_chord or reharmonize, though the name suggests generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. The only hint is the voice-leading tip for previousNotes, but there are no exclusions or explicit alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reharmonizeAReharmonize a progression. Techniques: tritone_sub, ii_v_insertion, modal_interchange, diminished_passing, secondary_dominant, chain_of_dominants, coltrane_changes, backdoor (or auto).
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | ||
| technique | No | ||
| progression | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds a list of techniques, which is useful, but it does not disclose behavioral traits beyond what annotations provide. Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description does not explain the return format, what 'auto' does, or how the transformation is applied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences, front-loaded with the primary action, and uses a clear, enumerative list for techniques. No redundant or repetitive wording. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has moderate complexity, and annotations cover safety, but there is no output schema. The description lacks details on return values, progression format, or the meaning of techniques like 'coltrane_changes'. It provides the essential purpose and options but is not comprehensive enough for correct invocation without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for parameter meaning. It explains the 'technique' parameter by listing valid values, and 'progression' is implied via the main action. However, the 'key' parameter is entirely undocumented, and the format of 'progression' (e.g., chord symbols) is not specified. Partial compensation but significant gaps remain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Reharmonize a progression.' The verb 'reharmonize' is specific and the resource 'progression' is explicit. The list of techniques distinguishes it from sibling tools like analyze_chord or resolve_chord, making the tool's unique function clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reharmonizing chord progressions but does not explicitly state when to use this tool versus alternatives like analyze_chord or generate_voicing. It lists techniques but offers no guidance on choosing between them or when not to use the tool. Context is clear but exclusions and alternatives are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolve_chordAResolve a chord to spelled notes, frequencies, MIDI, and recommended scales.
| Name | Required | Description | Default |
|---|---|---|---|
| chord | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the output categories (notes, frequencies, MIDI, scales) but no additional behavioral constraints or edge cases. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with zero filler. It conveys the core action and outputs efficiently, and every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, read-only), and the description covers purpose and output categories. However, it omits input format and output structure, and there is no output schema to compensate. The missing chord-notation detail is a clear gap, making this minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema defines only a 'chord' string with no description or format. Schema description coverage is 0%, and the description merely says 'a chord' without specifying accepted notation (e.g., 'Cmaj7', 'C major', note list). This is a significant gap for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Resolve') with a clear resource ('a chord') and explicitly enumerates the outputs: spelled notes, frequencies, MIDI, and recommended scales. This distinguishes it from siblings like analyze_chord, generate_voicing, and reharmonize, which have different outputs/purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage—use when you need chord resolution to notes/frequencies/scales—but provides no explicit guidance on when to prefer this tool over siblings or any exclusions. There is no mention of alternatives or prerequisites, so the guidance is only implicit.
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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