Agent skill

Lindy Reference Architecture

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Reference architectures for Lindy AI agent integrations. An agent skill from jeremylongshore/tons-of-skills-marketplace.

MITAuto-check passedBackend & APIs

Install Lindy Reference Architecture

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-reference-architecture -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace lindy-reference-architecture --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/lindy-reference-architecture .claude/skills/lindy-reference-architecture && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lindy-reference-architecture
GitHub stars
2.8k
Token cost
~3.2k tokens
SKILL.md length
1,077 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Reference architectures for Lindy AI agent integrations. An agent skill from jeremylongshore/tons-of-skills-marketplace.

  • Works in 6 steps: Write the workload's trust boundaries… → Record data classification, maximum… → Select the smallest pattern below that… → …
  • Designing systems
  • SKILL.md covers Overview, Prerequisites, Instructions and Trust-Boundary Contract, plus 11 more sections
  • Reaches public.lindy.ai

What it does

Lindy Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Reference architectures for Lindy AI agent integrations. Use when designing systems, planning multi-agent architectures, or implementing production integration patterns. Trigger with phrases like "lindy architecture", "lindy design", "lindy system design", "lindy patterns", "lindy multi-agent".

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/implementation-guide.md`). Compatibility notes: Portable instructions for agent harnesses that can read Markdown and edit architecture documents

It sits in Backend & APIs, covering Third-party API integration and Multi-agent orchestration. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Designing systems
  • Planning multi-agent architectures
  • Implementing production integration patterns
  • With phrases like lindy architecture

Example prompts

  • “lindy architecture”
  • “lindy design”
  • “lindy system design”
  • “/lindy-reference-architecture”

Requirements

  • Compatibility (from SKILL.md): Portable instructions for agent harnesses that can read Markdown and edit architecture documents
  • Pre-approved tools (allowed-tools): Read, Write, Edit

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Write the workload's trust boundaries before selecting a pattern: event producers,
  2. Record data classification, maximum payload size, expected event rate, recovery
  3. Select the smallest pattern below that meets those requirements. Treat product
  4. For every webhook edge, require HTTPS, an exact approved hostname, a per-edge
  5. Test authorized and unauthorized requests with synthetic data. A 2xx response is
  6. Produce the architecture decision record and dataflow inventory described in

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • public.lindy.ai

    Also links to:

    • docs.lindy.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Portable instructions for agent harnesses that can read Markdown and edit architecture documents

    From compatibility in the SKILL.md frontmatter.

Context cost

Lindy Reference Architecture loads about 3.2k tokens when it runs, and up to ~5.3k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 1,077 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 1,077 words, ~3,219 tokens.

Download SKILL.mdSave it as .claude/skills/lindy-reference-architecture/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
lindy-reference-architecture
description
Reference architectures for Lindy AI agent integrations. Use when designing systems, planning multi-agent architectures, or implementing production integration patterns. Trigger with phrases like "lindy architecture", "lindy design", "lindy system design", "lindy patterns", "lindy multi-agent".
allowed-tools
Read, Write, Edit
compatibility
Portable instructions for agent harnesses that can read Markdown and edit architecture documents
version
1.20.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, lindy, lindy-reference

Lindy Reference Architecture

Overview

Choose an integration shape for Lindy workflows without inventing a public SDK or control-plane API. The supported application boundary in these patterns is a dashboard-created Lindy webhook trigger, optionally paired with Lindy's HTTP Request or callback action for outbound delivery.

Prerequisites

  • Understanding of Lindy agent model (triggers, actions, skills)
  • Familiarity with webhook-based architectures
  • Production requirements defined (throughput, latency, reliability)
  • Current workspace evidence for the triggers, actions, integrations, and plan entitlements you intend to use
  • A separate secret for each Lindy trigger and a different secret for each callback receiver; neither belongs in source control or architecture diagrams

Instructions

  1. Write the workload's trust boundaries before selecting a pattern: event producers, Lindy trigger, callback receiver, stores, operators, and third parties.
  2. Record data classification, maximum payload size, expected event rate, recovery objective, and whether duplicate delivery is safe.
  3. Select the smallest pattern below that meets those requirements. Treat product features as available only after verifying them in the current Lindy workspace.
  4. For every webhook edge, require HTTPS, an exact approved hostname, a per-edge secret, schema validation, payload bounds, idempotency, bounded retry, and a dead-letter or manual recovery path.
  5. Test authorized and unauthorized requests with synthetic data. A 2xx response is insufficient evidence unless the expected task or durable queue record exists.
  6. Produce the architecture decision record and dataflow inventory described in Output, then have a security reviewer approve the exact deployment revision.

Trust-Boundary Contract

  • A Lindy trigger URL is created in the dashboard and uses the documented https://public.lindy.ai/api/v1/webhooks/... shape. Validate https: and the exact public.lindy.ai hostname before attaching its Lindy-generated trigger secret.
  • Authenticate your own event ingress independently. Do not reuse a Lindy trigger secret to protect your application or callback endpoint.
  • Minimize and redact event data before enqueueing it. Do not forward credentials, session tokens, raw customer records, or unrestricted third-party webhook bodies.
  • Acknowledge external events only after a durable, idempotent queue write. Check the Lindy response before marking delivery successful, and retry only transient failures with a strict attempt and elapsed-time budget.
  • Installed skills and local configuration are consumers of this design; they are not publication sources and must never upload secrets or runtime state.

Architecture 1: Simple Webhook Integration

Single agent triggered by your application, results sent via callback.

┌─────────────┐       POST (webhook)       ┌──────────────┐
│  Your App   │ ─────────────────────────→  │ Lindy Agent  │
│             │                             │              │
│  /callback  │ ←─────────────────────────  │ HTTP Request │
│             │       POST (callback)       │   Action     │
└─────────────┘                             └──────────────┘

Implementation:

  • Your app sends a bounded request to its dashboard-created Lindy webhook using that trigger's Lindy-generated bearer secret.
  • When a response is required, pass an allowlisted callback URL or opaque callback ID.
  • The Lindy workflow uses the currently available callback or HTTP Request action. Your callback receiver verifies its own distinct secret and accepts only the documented response schema.

Best for: Simple automations (email triage, lead scoring, content generation)

Architecture 2: Event-Driven Pipeline

Multiple event sources feed agents through a central webhook router.

┌──────────┐
│ Stripe   │──webhook──┐
└──────────┘           │
                       ▼
┌──────────┐     ┌───────────┐     ┌──────────────┐
│ Shopify  │──→  │  Router   │──→  │ Lindy Agents │
└──────────┘     │  Service  │     │              │
                 └───────────┘     │ • Order Bot  │
┌──────────┐           ▲          │ • Support Bot│
│ Your App │──webhook──┘          │ • Analytics  │
└──────────┘                      └──────────────┘

Implementation:

text
authenticated producer
  -> schema and size validation
  -> field allowlist and redaction
  -> idempotent durable queue
  -> route chosen from a static event-to-trigger map
  -> exact HTTPS/public.lindy.ai sink check
  -> attach only that route's trigger secret
  -> bounded delivery and response validation
  -> receipt with event ID, route, attempt count, and status (never payload/secret)

Keep the event-to-trigger map in trusted configuration rather than request data. The downloadable implementation guide contains a secure sender boundary; it deliberately uses documented webhook primitives rather than an assumed SDK client.

Best for: Multiple event sources, different agents per event type

Architecture 3: Multi-Agent Society (Delegation)

Specialized workflows collaborate through the agent-to-agent actions or webhook edges that are visibly available in the current workspace. Do not assume an action name, delivery guarantee, or universal delegation entitlement from this document.

┌─────────────────┐
│ Orchestrator    │
│ Lindy           │
│ (receives       │
│  initial task)  │
└───┬────────┬────┘
    │        │
    ▼        ▼
┌────────┐ ┌────────┐
│Research│ │Analysis│
│ Lindy  │ │ Lindy  │
└───┬────┘ └───┬────┘
    │          │
    ▼          ▼
┌─────────────────┐
│ Writer Lindy    │
│ (synthesizes    │
│  final output)  │
└─────────────────┘

Setup in Lindy:

  1. Define one bounded contract per specialist: accepted fields, result schema, timeout, and failure owner.
  2. Select a currently supported agent-to-agent action or the secured webhook pattern.
  3. Pass only the fields the specialist needs and correlate every result with a task ID.
  4. Require the orchestrator to handle timeout, partial completion, duplicate results, and human escalation before synthesis.

Key decisions:

DecisionOption AOption B
Context passingFull context (accurate, expensive)Selective context (cheap, focused)
Error handlingAgent retriesOrchestrator retry logic
ParallelismSequential delegationParallel delegation with merge

Best for: Complex tasks requiring multiple specialties (research + analysis + writing)

Show full SKILL.md (431 more words)Show less

Architecture 4: Scheduled Pipeline

Agents run on schedules, each feeding data to the next.

                    Schedule: Daily 6 AM
                         │
                         ▼
                  ┌──────────────┐
                  │ Data Fetch   │ Pulls from APIs/databases
                  │ Lindy        │
                  └──────┬───────┘
                         │ Agent Send Message
                         ▼
                  ┌──────────────┐
                  │ Analysis     │ Processes & summarizes
                  │ Lindy        │
                  └──────┬───────┘
                         │ Agent Send Message
                         ▼
                  ┌──────────────┐
                  │ Report       │ Formats & delivers
                  │ Lindy        │
                  │  → Slack     │
                  │  → Email     │
                  └──────────────┘

Best for: Daily reports, weekly digests, scheduled data processing

Architecture 5: Chat + Knowledge Base

Agent exposed through a chat surface currently supported by the workspace and grounded in an approved knowledge base.

┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│  Website     │     │ Lindy Agent  │     │ Knowledge    │
│  (Embed      │◀──▶ │              │◀──▶ │ Base         │
│   Widget)    │     │ Chat Trigger │     │ PDFs, Docs,  │
└──────────────┘     │ + KB Search  │     │ Websites     │
                     │ + Condition  │     └──────────────┘
                     │ + Escalate   │
                     └──────────────┘
                            │
                            ▼ (if escalation needed)
                     ┌──────────────┐
                     │ Slack DM to  │
                     │ human agent  │
                     └──────────────┘

Deployment boundary:

  • Publish only through a chat or embed surface shown in current Lindy documentation or the workspace UI; do not paste an unverified script URL from a template.
  • Approve each knowledge source, record its owner and refresh cadence, and test that revoked or sensitive documents are not retrievable.
  • Configure result count and matching behavior from measured answer quality rather than hard-coded template values.
  • Add human escalation and an explicit no-answer path before public exposure.

Best for: Customer support, FAQ bots, internal knowledge assistants

Architecture Decision Matrix

PatternChoose whenMeasure before approvalPrimary risk
Simple webhookOne bounded async workflowend-to-end latency, duplicate ratecallback spoofing
Event-driven pipelineMultiple producers or replay requiredqueue lag, retry volumeevent/data fan-out
Multi-agent workflowSpecialist boundaries improve qualitycompletion rate, context sizeauthority drift
Scheduled pipelineWork is naturally periodicfreshness, missed-run recoverysilent schedule gaps
Chat + knowledge baseUsers need interactive retrievalanswer quality, escalation ratesensitive retrieval

Error Handling

PatternFailure ModeRecovery
Simple webhookAgent fails or callback is rejectedretain receipt; retry within budget; escalate
Event-drivenRouter or downstream unavailablekeep durable event; replay idempotently
Multi-agentSpecialist times out or returns invalid datastop synthesis or use approved partial-result policy
ScheduledRun is missedalert; perform an explicit catch-up run if safe
Chat + KBEvidence is absent or access is deniedsay no answer; escalate without exposing hidden data

Output

Return two reviewable artifacts:

  1. Architecture decision record: chosen pattern, alternatives rejected, current Lindy capabilities verified, capacity assumptions, failure policy, rollback trigger, owners, and review date.
  2. Dataflow and trust-boundary inventory: every edge's producer, destination, allowed schema, classification, authentication owner, secret scope, size/rate bound, idempotency key, retention, log policy, and recovery path.

No output may contain webhook URLs, bearer values, customer payloads, or copied runtime configuration. Use route names and redacted identifiers in diagrams and receipts.

Examples

For an order-triage workflow, choose the event-driven pattern and record:

yaml
decision: event-driven-webhook
event: order.created.v1
allowed_fields: [event_id, order_id, country_code, risk_band]
durable_before_ack: true
idempotency_key: event_id
trigger_route: lindy-order-triage
trigger_sink: https/public.lindy.ai
callback_auth: distinct-from-trigger
retry_budget: "3 attempts within 5 minutes"
rollback: "pause consumer and retain queued events"
evidence: "authorized task created; unauthorized request created no task"

The record names the sink class, not the unique webhook path, and includes no order contents or credentials. A reviewer can reproduce both the accepted and rejected paths with synthetic IDs before production traffic is enabled.

Resources

Next Steps

Proceed to Flagship tier skills for enterprise features: multi-env, observability, incident response, data handling, RBAC, and migration.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/lindy-reference-architecture of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/implementation-guide.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Lindy Reference Architecture next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Lindy Reference Architecture compared with similar skills
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Mission Control Agent APIbuilderz-labs/mission-control6.3k—~2.1kAutomated safety check: PassMIT
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Questions about Lindy Reference Architecture

What does Lindy Reference Architecture do?

Reference architectures for Lindy AI agent integrations. An agent skill from jeremylongshore/tons-of-skills-marketplace. Lindy Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Reference architectures for Lindy AI agent integrations.

When should I use Lindy Reference Architecture?

Lindy Reference Architecture fits situations like: designing systems; planning multi-agent architectures; implementing production integration patterns; with phrases like lindy architecture.

How do I install Lindy Reference Architecture in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-reference-architecture -a claude-code`. Or copy the skill folder (skills/.curated/lindy-reference-architecture in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/lindy-reference-architecture in your project. Claude Code loads it when a task matches its description.

How do I install Lindy Reference Architecture in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-reference-architecture -a codex`. Or copy the skill folder (skills/.curated/lindy-reference-architecture in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/lindy-reference-architecture in your project. Codex loads it when a task matches its description.

Can I use Lindy Reference Architecture in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill lindy-reference-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lindy-reference-architecture, .gemini/skills/lindy-reference-architecture, .github/skills/lindy-reference-architecture and .opencode/skills/lindy-reference-architecture in your project.

What does Lindy Reference Architecture need to run?

SKILL.md names no scripts, command-line tools or credentials: Lindy Reference Architecture is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit. Compatibility (from SKILL.md): Portable instructions for agent harnesses that can read Markdown and edit architecture documents.

Does Lindy Reference Architecture access the network?

SKILL.md names 2 domains. In commands or code: public.lindy.ai; the agent is likely to contact it when it follows the instructions. As links in the text: docs.lindy.ai. This is read from the text; nothing was executed.

Is Lindy Reference Architecture safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Lindy Reference Architecture use?

Lindy Reference Architecture is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lindy Reference Architecture use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Lindy Reference Architecture?

Skills that share tags, products or a category with Lindy Reference Architecture: DeerFlow HTTP API Client (bytedance/deer-flow, 84k stars), Mission Control Agent API (builderz-labs/mission-control, 6.3k stars), MCP API Key Authentication (Yourdaylight/stock_datasource, 189 stars) and Atlassian MCP Expert (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lindy Reference Architecture?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.