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 Rijul1204/rashedul-agentic-engineering --skill recall-ai-integrationgit clone --depth 1 https://github.com/Rijul1204/rashedul-agentic-engineeringWrote 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/rijul1204/rashedul-agentic-engineering/recall-ai-integration)<a href="https://agentmods.dev/skills/rijul1204/rashedul-agentic-engineering/recall-ai-integration"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/recall-ai-integration/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/rijul1204/rashedul-agentic-engineering/recall-ai-integration"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/recall-ai-integration.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 | $0.00253 | $0.02029 |
| Opus 5 | $0.00127 | $0.01014 |
| Sonnet 5 | $0.00051 | $0.00406 |
| Haiku 4.5 | $0.00025 | $0.00203 |
Grade A, and why
recall-ai-integration 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 10d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recall.ai Integration
Recall.ai is a meeting-bot vendor — you dispatch a bot to a Google Meet / Zoom / Teams URL, it joins, captures audio + transcripts, accepts commands (speak, chat, leave), and webhooks you status + realtime events. This skill also covers two closely-coupled ElevenLabs surfaces — Scribe (Recall's recording_config.transcript.provider alternate to meeting_captions) and Voice (the documented TTS swap target) — because the wire-contract rules and quality gates apply identically and the swaps tend to live next to each other in the codebase.
Why this skill exists. Two real production incidents (May 2026) — in_call_recording.data was assumed to be a scalar when it's a nested object, and an OpenAI Realtime route 502'd because the session schema changed silently — both traced to the same root cause: code written from training-memory intuition instead of from a live doc read + sandbox probe. This skill exists so the next agent reads + probes before coding.
The skill is modular. The body below is a manifest; depth lives in references/. Load only what the current task needs.
Portability note
This skill was extracted from a Next.js + TypeScript codebase. The reference files cite example file paths (e.g. lib/meet/bot-client.ts, app/api/meet/webhook/status/route.ts, synthesizeSpeech, MeetingBotClient) to make the contracts concrete. These are examples of where the vendor seam might live, not paths that need to exist in your repo. Map them to your own structure as you read:
- "
MeetingBotClient" / "bot-client.ts" → your single wrapper class around all Recall HTTP calls (so the documented Attendee fallback stays a one-class swap). - "
synthesizeSpeech" / "lib/meet/tts.ts" → your single seam for TTS (so the OpenAI ↔ ElevenLabs Voice swap is local). - "
/api/meet/webhook/status" / "/api/meet/webhook/realtime" → your two webhook routes for Recall's two channels. - "
Personal_Docs/..." prefixes → your app root.
What ships with it
11 files 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.
- references/api-reference.md 7.1 KB
- references/architecture.md 8.6 KB
- references/auth-and-env.md 7.4 KB
- references/elevenlabs.md 8.6 KB
- references/gotchas.md 7.7 KB
- references/README.md 2.1 KB
- references/recipes-add-endpoint.md 6.3 KB
- references/refusals.md 6.8 KB
- references/webhooks.md 7.3 KB
- references/workflow-bug-fix.md 8.3 KB
- references/workflow-feature.md 8.2 KB
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.
- 10d ago First seen · 101 lines · 253 tokens per session scan A 8f2451b3d96d
recall-ai-integration is a skill published in the GitHub repository Rijul1204/rashedul-agentic-engineering (2 stars, last pushed 1mo ago), licensed MIT. It adds 253 tokens to every session and 2,029 once invoked, about $0.0013 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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