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building-ai-agent-on-cloudflare

Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

86

1.00x
Quality

78%

Does it follow best practices?

Impact

100%

1.00x

Average score across 3 eval scenarios

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/cloudflare/skills/building-ai-agent-on-cloudflare/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A generally strong, code-forward body: concrete Agents SDK examples, real wrangler/entry-point config, and well-signaled one-level-deep references that all exist. Weaknesses are moderate padding (conceptual and duplicate sections), minor compile gaps in the flagship code sample, and a topic-oriented structure that lacks an explicit build-validate-deploy workflow with error feedback.

Suggestions

Cut or trim the "What is an Agent?", "When to Use", and "Reading State" sections — the first explains concepts Claude already knows, the second duplicates the description's Use-when clause, and the third shows trivial property access; fold the State Management/SQL inline section into references/state-patterns.md to reduce body length.

Make the flagship Basic Agent Structure sample fully executable: add the missing `Ai` type import (or show the `@cloudflare/workers-types` import) so the snippet compiles as written.

Restructure the build flow as an explicit sequence with a validation checkpoint — e.g. scaffold → implement → `npm start` and verify `http://localhost:8787` responds → `npx wrangler deploy` → `curl` the deployed agent → on failure, see references/troubleshooting.md — so error recovery is part of the workflow rather than a separate pointer.

DimensionReasoningScore

Conciseness

The bulk is SDK-specific code and config Claude cannot safely assume, but several sections are unnecessary: "What is an Agent?" explains generic concepts ("Maintains state across requests... Scales horizontally"), "When to Use" restates the description's Use-when clause, "Reading State" shows trivial property access, and comments like "// Called when agent starts or resumes" pad obvious code. Fits the mostly-efficient-with-some-unnecessary-explanation anchor; not 2 because the padding is a minority of the ~390 lines and most tokens carry SDK-specific value.

3 / 5

Actionability

Concrete, mostly copy-paste-ready TypeScript, wrangler TOML, bash commands, and WebSocket URLs covering the common cases (basic agent, entry point, config, chat agent, clients). Minor gaps keep it below 5: `Ai` is referenced in `interface Env { AI: Ai; }` without an import, and the ChatBot example relies on an `Env` defined only in an earlier section — as written, the basic structure snippet does not compile standalone.

4 / 5

Workflow Clarity

The body is organized by topic rather than as a sequenced build workflow, and checkpoints are implicit: Quick Start → structure → config → deploy is implied by section order, but validation is limited to a single `curl` test in Deployment with no verify-after-deploy or error-recovery loop (troubleshooting is pointed to but not woven into a feedback cycle). Fits 'sequence present but checkpoints missing or implicit'; not 4 because the deploy-then-test step lacks a failure path back to troubleshooting.

3 / 5

Progressive Disclosure

All four referenced files (agent-patterns.md, examples.md, state-patterns.md, troubleshooting.md) exist, are exactly one level deep (no nested references), and are clearly signaled both inline and in a References section. Minor gap: ~50 lines of State Management/SQL Storage inline in the body overlap ground also covered by references/state-patterns.md ("How State Works", "Hybrid Pattern"), which is more than ideal placement; not 3 because the split is still complementary (core API inline, patterns external) and navigation is easy.

4 / 5

Total

14

/

20

Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person voice, concrete and comprehensive capability list, and an explicit 'Use when' clause with natural quoted trigger phrases. The only weakness is that several trigger terms are platform-agnostic agent-building phrases that create minor conflict risk with non-Cloudflare agent skills.

DimensionReasoningScore

Specificity

"Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities" plus "Generates production-ready agent code deployed to Workers" lists multiple concrete, domain-specific actions with comprehensive coverage. Not 4: the capability list spans all the skill's major functions with no notable gaps.

5 / 5

Completeness

Both are explicit: the what ("Builds AI agents on Cloudflare using the Agents SDK... Generates production-ready agent code deployed to Workers") and the when ("Use when: user wants to 'build an agent'..." with concrete trigger phrases). This matches the score-5 anchor exactly; the 'Use when' clause is explicit and specific, ruling out 4.

5 / 5

Trigger Term Quality

Quoted trigger phrases include "build an agent", "AI agent", "chat agent", "stateful agent", "Agents SDK", "real-time AI", "WebSocket AI", "state management", "scheduled tasks", and "tool calling" — natural user phrasings with synonym coverage. No relevant natural term is missing; not 4 because coverage extends across capability, technology, and intent variants.

5 / 5

Distinctiveness Conflict Risk

"Cloudflare", "Agents SDK", and "Workers" establish a clear niche, but generic triggers like "build an agent", "AI agent", and "chat agent" could also fire for agent-building requests on other platforms or providers. Mostly distinct with minor overlap risk against closely related agent skills, fitting the score-4 anchor; not 5 because the broad agent triggers are not platform-qualified.

4 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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