Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add RasaHQ/rasa-agent-skills --skill rasa-integrating-ttsgit clone --depth 1 https://github.com/RasaHQ/rasa-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rasahq/rasa-agent-skills/rasa-integrating-tts)<a href="https://agentmods.dev/skills/rasahq/rasa-agent-skills/rasa-integrating-tts"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-integrating-tts/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rasahq/rasa-agent-skills/rasa-integrating-tts"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-integrating-tts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01086 |
| Opus 5 | $0.00031 | $0.00543 |
| Sonnet 5 | $0.00012 | $0.00217 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
rasa-integrating-tts scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Integrating a Custom TTS Provider
The provider documentation is: $documentation
Use the documentation as the source of truth for the provider protocol. If it is missing, ask for the provider's TTS API documentation before implementing. Follow links from it only when needed to resolve authentication, request/response messages, audio formats, streaming behavior, interruption, or limits.
Workflow
- Inspect the assistant's installed Rasa version and the actual
TTSEngine,TTSEngineConfig, andRasaAudioBytesAPIs. Follow those signatures when they differ from examples. - Review existing custom speech components and project conventions before choosing a
module path. Default to
addons/custom_tts.pyonly when no convention exists. - Read the provider documentation and complete the protocol analysis in references/integration-framework.md.
- Choose streaming or non-streaming input from documented provider behavior. Do not mark an engine as streaming merely because its response audio arrives in chunks.
- Design the configuration and audio conversion, then implement the custom
TTSEngine. - Configure its fully qualified class path under the voice channel's
ttskey incredentials.yml. Keep secrets in environment variables. - Add focused tests for configuration, request messages, audio conversion, lifecycle, and provider errors.
- Run the project's relevant tests, lint/type checks, and Rasa configuration validation. Report any validation that could not be run.
Select the synthesis mode
Use non-streaming input when the provider requires the complete text before synthesis:
- keep
streaming_inputfalse; - implement
synthesize()as the complete text-to-audio lifecycle; - yield
RasaAudioBytesas provider audio becomes available.
Use streaming input only when the provider accepts multiple incremental text chunks in one synthesis session:
- set
streaming_input = True; - implement the installed contract's connection, text-chunk, text-done, and audio streaming methods;
- preserve ordering and flush semantics documented by the provider.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 117 lines · 62 tokens per session scan A 804cfc1ed0cf
rasa-integrating-tts is a skill published in the GitHub repository RasaHQ/rasa-agent-skills (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,086 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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