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 agentmods add skills/langbot-app/langbot/langbot-eba-adapter-devnpx skills add langbot-app/LangBot --skill langbot-eba-adapter-devgit clone --depth 1 https://github.com/langbot-app/LangBotWrote 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/langbot-app/langbot/langbot-eba-adapter-dev)<a href="https://agentmods.dev/skills/langbot-app/langbot/langbot-eba-adapter-dev"><img src="https://agentmods.dev/badge/skills/langbot-app/langbot/langbot-eba-adapter-dev.svg" alt="Measured on agentmods" 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 | $0.00073 | $0.03516 |
| Opus 5 | $0.00036 | $0.01758 |
| Sonnet 5 | $0.00015 | $0.00703 |
| Haiku 4.5 | $0.00007 | $0.00352 |
Grade A, and why
langbot-eba-adapter-dev 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 4d 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LangBot EBA Adapter Development
Use this skill when implementing or reviewing a LangBot platform adapter under the Event-Based Agents architecture.
Controlling a running instance via MCP
Beyond writing code, you can drive a live LangBot instance over MCP — no raw
HTTP needed. Two MCP servers exist (both reuse existing API keys; see AGENTS.md):
- LangBot instance —
http://<host>:5300/mcp(auth: web-UIlbk_key or theapi.global_api_keyfromconfig.yaml). Manage bots, pipelines, models, knowledge bases, and skills. See thelangbot-mcp-opsskill. - LangBot Space marketplace —
https://space.langbot.app/mcp(auth: Personal Access Token). Search plugins / MCP servers / skills. See thelangbot-space-opsskill.
Any change to an agent-accessible HTTP API endpoint must keep the matching MCP tool and these skills in sync.
Core Rule
Do not let platform-native event or message shapes leak into LangBot's common path. Each adapter must convert incoming SDK objects into unified EBA entities before dispatch:
- Events:
langbot_plugin.api.entities.builtin.platform.events - Message chains:
langbot_plugin.api.entities.builtin.platform.message.MessageChain - Users/groups/members:
langbot_plugin.api.entities.builtin.platform.entities - Raw platform objects may remain only in
source_platform_objectfor debugging or platform-specific escape hatches.
Start Here
- Read the EBA design docs in
LangBot/docs/event-based-agents/. - Read the architecture-level acceptance checklist before writing or validating code:
LangBot/docs/event-based-agents/adapters/acceptance-checklist.md
- Read the current reference adapter before writing code. Prefer Telegram first:
LangBot/src/langbot/pkg/platform/adapters/telegram/LangBot/docs/event-based-agents/adapters/telegram.md
- Read the legacy source adapter for the target platform:
LangBot/src/langbot/pkg/platform/sources/<platform>.pyLangBot/src/langbot/pkg/platform/sources/<platform>.yaml
- Inspect SDK entity definitions in
langbot-plugin-sdk/src/langbot_plugin/api/entities/builtin/platform/. - Search before assuming APIs. Platform SDKs change often.
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.
- 4d ago First seen · 302 lines · 73 tokens per session scan A bd83f1e8b2bc
langbot-eba-adapter-dev is a skill published in the GitHub repository langbot-app/LangBot (17,643 stars, last pushed today), licensed Apache-2.0. It adds 73 tokens to every session and 3,516 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
html-artifacts
Author the HTML for a plan artifact, dashboard iframe, or Slack attachment — structure, design plan, available runtime, theming, and craft. Read this before writing HTML for saveplan, outputiframe, or slackattachhtml.
bootstrap-repo-analysis
First-time analysis of a repository with no prior reviewer outcomes. Crawl historical merged-PR review feedback with the gh CLI (plus any preloaded samples), extract the team's review norms, and synthesize the initial per-repo review-style prompt. Use this for a cold-start repo; use continual-learning instead once the…
baby-sit
Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.
continual-learning
Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…
search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
frontend-code-review
Use only when the user explicitly requests a review or audit of frontend code under web/ or packages/dify-ui/. Supports pending-change, file-focused, and pasted-diff reviews. Do not use for implementation-only requests, diagnosis without review intent, or backend-only code.