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music-generation

Generate music using ElevenLabs Music through Letta. Use when creating instrumental tracks, songs with lyrics, background music, jingles, theme songs, or any AI-generated music composition. Supports prompt-based generation and composition plans for section-by-section control.

Quality

88%

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A high-quality, tightly written API skill: executable examples cover the common cases, validation and error-recovery guidance are explicit, and provider-specific details (Letta endpoint, credits, restrictions) are all things Claude would not know. The main improvement opportunities are consolidating the implicit workflow into a clearer ordered flow and moving legacy v1 details out of the main file.

DimensionReasoningScore

Conciseness

The body is dense with non-obvious, provider-specific facts (Letta endpoint and credit rules, stream vs non-stream behavior, chunk limits, error semantics) and avoids explaining concepts Claude already knows. A few passages could be trimmed — the adaptation/licensing paragraph and the "share the saved file the way your current surface supports" surface guidance — so it fits anchor 4 rather than anchor 5's every-token-earns-its-place.

4 / 5

Actionability

Fully executable guidance throughout: a copy-paste curl Quick Start with env-var handling and status-code interpretation, a complete JSON composition plan example, a model ID table, concrete output_format values, and error codes with specific retry actions and suggestion fields. This matches anchor 5's copy-paste-ready coverage of common cases.

5 / 5

Workflow Clarity

The flow (build request → POST to the stream endpoint → verify 200 with an audio content type → read the JSON error if not → share or retry) is unambiguous, with explicit validation and feedback loops (retry with prompt_suggestion/composition_plan_suggestion, retry once on 500, never retry 402, retry truncated streams). However, the sequence is distributed across reference-style sections rather than laid out as an ordered workflow, with credit/length pre-checks split between "Length" and "Error Handling", fitting anchor 4 rather than 5.

4 / 5

Progressive Disclosure

No bundle files exist; the single-file skill is well-sectioned with clear headers and no nested references, so navigation is easy. Minor organization gaps remain — the legacy music_v1 plan format and the output-format table are inlined content that could live in a separate reference, and the skill exceeds the under-50-line simple-skill exception — fitting anchor 4.

4 / 5

Total

17

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person voice, explicit "Use when..." triggers covering the natural music-generation vocabulary, a clear statement of what the skill does, and a distinct niche. The only room for improvement is slightly broader capability enumeration and a few more natural synonyms.

DimensionReasoningScore

Specificity

"Generate music", "prompt-based generation and composition plans for section-by-section control" name the domain plus several concrete generation modes and output types (instrumental tracks, songs with lyrics, background music, jingles, theme songs). It lists several specific actions with minor gaps rather than anchor 5's comprehensive action coverage, since capabilities like length control, seeds, and output formats are unnamed.

4 / 5

Completeness

It explicitly answers both: "Generate music using ElevenLabs Music through Letta... Supports prompt-based generation and composition plans for section-by-section control" (what) and "Use when creating instrumental tracks, songs with lyrics, background music, jingles, theme songs, or any AI-generated music composition" (when), with concrete trigger phrases matching the anchor 5 example pattern.

5 / 5

Trigger Term Quality

"instrumental tracks", "songs with lyrics", "background music", "jingles", "theme songs", "music composition" give good natural keyword coverage a user would actually say. Falls short of anchor 5's synonym-and-extension completeness: common phrases like "make a song", "soundtrack", "beat", or "melody" are missing.

4 / 5

Distinctiveness Conflict Risk

"ElevenLabs Music through Letta" plus music-specific triggers ("jingles", "theme songs", "background music") establish a clear niche with minimal conflict risk against adjacent audio/speech-generation skills.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

letta-ai/letta-code

Path

src/skills/builtin/music-generation/SKILL.md

Reviewed

Table of Contents

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