Update Chapter. Updates a chapter.
Bulk support: accepts project_ids, chapter_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| account | No | ||
| content | No | ||
| chapter_id | Yes | ||
| project_id | Yes | ||
| chapter_ids | No | ||
| project_ids | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal that this is not read-only (readOnlyHint=false), and the description adds a useful behavioral trait: bulk execution via project_ids and chapter_ids. However, it does not disclose whether updates are partial or full replacements, what happens to omitted fields, or any side effects beyond 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 short and front-loaded, but the opening 'Update Chapter. Updates a chapter.' is redundant and wastes words. The bulk-support sentence is concise and useful. Overall, it is compact but contains repetition that reduces efficiency.
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 no output schema and 0% schema description coverage, the description is too minimal for a tool with 7 parameters including a nested content object. It does not explain return values, update semantics, or how the content blocks should be structured, leaving significant gaps for an agent to resolve.
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 carries the burden of explaining parameters. It only adds meaning for chapter_ids and project_ids (batch execution), while leaving name, content, and account semantically unexplained. The complex content object structure is not described at all.
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 identifies the operation as updating a chapter, with 'Update Chapter. Updates a chapter.' providing a specific verb and resource. It is distinct from sibling tools like add_chapter and delete_chapter_endpoint, though it does not explicitly name alternatives. The redundancy between the first two sentences slightly weakens clarity.
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 statement 'Bulk support: accepts project_ids, chapter_ids for batched execution' gives a concrete usage feature, implying when batched updates are relevant. However, it does not explicitly state when to prefer this tool over alternatives like elevenlabs_edit_project or provide exclusions for non-bulk use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
There are many tools with overlapping purposes, such as multiple voice retrieval tools (get_voice_by_id, get_voices, get_user_voices_v2, get_library_voices) and several dubbing transcript segment editors with only subtle naming differences. The inclusion of platform-level tools (authenticate, connect, marketplace) alongside ElevenLabs API tools further blurs boundaries.
Naming is highly inconsistent. Most tools have the 'elevenlabs_' prefix, but some do not (authenticate, connect, marketplace, report_bug, show_version, toolkit_info). Several tools have truncated/random suffix names (e.g., elevenlabs_dubbing_target_transcript_segmen_b565e6, elevenlabs_get_pronunciation_dictionary_ver_45baf2), and one tool is in Portuguese (elevenlabs_list_accounts). This mixture of conventions and languages makes the pattern unpredictable.
With 155 tools, the server is extremely bloated. It mixes a comprehensive ElevenLabs API surface with unrelated MCP platform tools (marketplace, authenticate, report_bug, etc.) that belong in a separate toolkit. This is a severe mismatch between the apparent purpose (ElevenLabs audio services) and the sheer number of tools.
The ElevenLabs-specific tools cover a wide range of operations (text-to-speech, voice management, dubbing, pronunciation dictionaries, Studio projects, workspace administration, order management), making it fairly complete for those domains. However, the inclusion of unrelated platform tools and the lack of a clear focus mean that an agent would have difficulty navigating this large surface, and some operations like music finetuning or speech engines appear only partially covered.