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-asrgit 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-asr)<a href="https://agentmods.dev/skills/rasahq/rasa-agent-skills/rasa-integrating-asr"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-integrating-asr/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-asr"><img src="https://agentmods.dev/badge/skills/rasahq/rasa-agent-skills/rasa-integrating-asr.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 | $0.00056 | $0.01063 |
| Opus 5 | $0.00028 | $0.00531 |
| Sonnet 5 | $0.00011 | $0.00213 |
| Haiku 4.5 | $0.00006 | $0.00106 |
Grade A, and why
rasa-integrating-asr 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Integrating a Custom ASR 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 streaming ASR API documentation before implementing. Follow links from it only when needed to resolve authentication, WebSocket messages, audio formats, endpointing, or limits.
Workflow
- Inspect the assistant's installed Rasa version and the actual
ASREngine,ASREngineConfig,ASREvent, 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_asr.pyonly when no convention exists. - Read the provider documentation and complete the feasibility checks in references/integration-framework.md.
- If a hard requirement is unsupported or undocumented, report every incompatibility found and stop. Do not invent protocol messages, transcript semantics, or client-side endpointing.
- Design the configuration and event mapping, then implement the custom
ASREngine. - Configure its fully qualified class path under the voice channel's
asrkey incredentials.yml. Keep secrets in environment variables. - Add focused tests for provider-message mapping, transcript accumulation, audio conversion, and malformed/error events.
- Run the project's relevant tests, lint/type checks, and Rasa configuration validation. Report any validation that could not be run.
Feasibility gate
A custom ASR integration must have:
- a documented real-time streaming API compatible with the
ASREngineconnection lifecycle; - a documented end-of-utterance or end-of-turn signal that can produce exactly one
NewTranscript; - an audio encoding and sample rate that the provider accepts directly or that can be
converted safely from
RasaAudioBytes; - documented authentication suitable for a server process;
- clear partial, final, error, and connection-close message semantics.
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 · 113 lines · 56 tokens per session scan A ff40ee2e9e28
rasa-integrating-asr is a skill published in the GitHub repository RasaHQ/rasa-agent-skills (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,063 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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