lark-openapi-explorer

lark-openapi-explorer is a skill for Claude Code, Codex from aws-samples/sample-lark-mcp-on-agentcore. It costs 71 tokens per session (1,425 once invoked), scanned A, original, MIT-0.

A way to explore Feishu (Lark) OpenAPI, the official programming interface for Feishu’s services. It helps find available endpoints that are not already covered by existing add-ons or commands.

In plain words
What is it for?
Searching official Feishu documentation for an unwrapped API endpoint and using that endpoint when a user’s task requires it.
Why use it?
It provides a route for requests that existing Feishu tools cannot handle.

Skill for Claude CodeCodex ✓ vendor

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Searching official Feishu documentation for an unwrapped API endpoint and using that…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aws-samples/sample-lark-mcp-on-agentcore/lark-openapi-explorer
About the project

aws-samples/sample-lark-mcp-on-agentcore is a hosted remote MCP service that lets AI agents use Feishu/Lark through lark-cli's tools and multi-step workflow skills. Teams can deploy one centrally managed service while individual members authorize their own Feishu identities, with the service running on AWS Bedrock AgentCore. The catalogue add-ons help agents perform Lark operations through this service.

aws-samples/sample-lark-mcp-on-agentcore · 11 stars · on GitHub

Install

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.

Any agent
npx skills add aws-samples/sample-lark-mcp-on-agentcore --skill lark-openapi-explorer
Clone the repo
git clone --depth 1 https://github.com/aws-samples/sample-lark-mcp-on-agentcore

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for lark-openapi-explorer

README.md
[![agentmods](https://agentmods.dev/badge/skills/aws-samples/sample-lark-mcp-on-agentcore/lark-openapi-explorer.svg)](https://agentmods.dev/skills/aws-samples/sample-lark-mcp-on-agentcore/lark-openapi-explorer)
Your own site
<a href="https://agentmods.dev/skills/aws-samples/sample-lark-mcp-on-agentcore/lark-openapi-explorer"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-lark-mcp-on-agentcore/lark-openapi-explorer.svg" alt="Measured on agentmods" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,425 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01425
Opus 5 $0.00036 $0.00713
Sonnet 5 $0.00014 $0.00285
Haiku 4.5 $0.00007 $0.00143

Measured 6d ago against content hash f0a464de1b8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

lark-openapi-explorer 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 6d 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.

docker/skills/lark-openapi-explorer/SKILL.md · 157 lines

The source is not reproduced here

Licensed MIT-0

The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Changes

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.

  1. 6d ago First seen · 157 lines · 71 tokens per session scan A f0a464de1b8f

Subscribe to this mod's changes

lark-openapi-explorer is a skill published in the GitHub repository aws-samples/sample-lark-mcp-on-agentcore (11 stars, last pushed 3d ago), licensed MIT-0. It adds 71 tokens to every session and 1,425 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.

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