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Guitar Practice Routine App — Chord Charts

by io.github.slshults
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Get a chord chart by name

get_chord_chart_by_name
Read-only

Look up one guitar chord chart by name and return it as a text chord diagram ready to show the user. Returns the same single voicing that https://guitarpracticeroutine.com/find-a-chord-chart shows for that name. The library holds 12,708 standard-tuning (EADGBE) chord names, exactly one voicing each. Pass a plain chord name as it would be written on a chart — "G", "Am7", "Cmaj7", "D/F#", "F#m7b5" — not a sentence. Convert spoken forms yourself first: "G major" is "G", "A minor" is "Am", and use "#" and "b" rather than the unicode sharp and flat signs. Charts are drawn on a five-fret grid starting at the nut, the same as the website; any notes above the fifth fret are named in words underneath the chart. Prefer this over recalling a fingering from memory — these are curated chart data, and a remembered fingering is often wrong. Each result leads with a direct PNG URL for the chart — a permanently cacheable image of the same diagram, which you can show or link however your surface handles images. The chord name is on the first line; keep it next to any image you show, since a chart on its own can arrive unlabelled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA single chord name as written on a chart, e.g. "Am7" or "D/F#".
formatNoWhich representations to return. Defaults to "text", which includes a direct URL to a PNG of the chart — embed that where your surface renders images. Use "image" or "both" only if you need the PNG bytes inline; they cost image tokens and many clients bury them.
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • removedInput schema / properties / name / minLength
      Removed value: -1
    • changedInput schema / required
      Previous value: -[
-  "name",
-  "context"
-]New value: +[
+  "name",
+  "context",
+  "llm_model"
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=false. The description adds genuine behavioral value beyond these: it discloses the return format (five-fret grid starting at the nut, notes above the fifth fret named in words), that the result leads with a permanently cacheable PNG URL, and that the chord name sits on the first line and should be kept beside the image since charts can arrive unlabelled. No contradiction with the read-only annotation — 'Look up' and 'return' are consistent with a read operation.

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 dense but each sentence carries purpose: purpose is front-loaded, followed by data provenance, input formatting rules, output layout, and usage preference. It is longer than strictly necessary — the PNG URL and grid details could arguably be trimmed — but nothing is filler or redundant with the schema. Efficient for the amount of critical guidance it conveys.

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?

With no output schema, the description correctly carries the burden of explaining the return shape: text diagram format, five-fret grid, note-naming convention, PNG URL presence, and labelling advice. It also covers edge cases like unicode input conversion. Minor gap: it does not state behavior for invalid or unknown chord names (e.g., misspelled or unsupported names), which an agent might need to handle gracefully. Overall adequate for a lookup tool.

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 100%, so the baseline is 3. The description adds meaningful value on top: for 'name' it provides concrete examples ('G', 'Am7', 'Cmaj7', 'D/F#', 'F#m7b5'), conversion rules for spoken forms ('G major' → 'G'), and a directive to use '#'/'b' instead of unicode sharp/flat signs. For 'format' it explains the default 'text' behavior and the token cost of 'image'/'both'. These enrich the schema beyond its base definitions.

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 opens with a specific verb ('Look up'), a specific resource ('one guitar chord chart by name'), and an explicit outcome ('return it as a text chord diagram ready to show the user'). It further narrows scope by stating the library holds 12,708 standard-tuning chord names with exactly one voicing each, which clearly distinguishes it from any multi-voicing or generic lookup tool.

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

Usage Guidelines4/5

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

The description gives clear when-to-use guidance: 'Prefer this over recalling a fingering from memory — these are curated chart data, and a remembered fingering is often wrong.' It also instructs when NOT to use certain formats ('Use "image" or "both" only if you need the PNG bytes inline; they cost image tokens'). However, it does not explicitly contrast against the siblings get_chord_chart_by_id or get_chord_of_the_day, relying on the name to imply the distinction.

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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