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honi

Build AI agents with Honi (honidev) on Cloudflare Workers. Use when creating agents with tools, persistent memory, MCP servers, or multi-agent pipelines. Covers createAgent API, tool() helper, all memory tiers (working/episodic/semantic/graph), multi-agent routing, MCP auth, and all supported model providers.

Quality

85%

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Critical

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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 well-structured, largely executable framework reference that respects the reader's intelligence and avoids teaching known concepts. Its main issues are one non-compiling multi-agent example, the absence of any deploy command, and a length that would benefit from moving provider/memory detail into reference files.

Suggestions

Fix the multi-agent example: 'export class SupportAgent extends SupportAgent {}' is a duplicate export of a self-referential class and will not compile — rename the exported class (e.g. 'export class SupportAgentDO extends SupportAgent {}') and update wrangler.toml's class_name to match.

Add the deployment step to close the workflow gap: a 'wrangler deploy' (and 'wrangler dev' for local testing) command after the minimal agent's wrangler.toml would make the install-to-live sequence complete.

Move the supported-models table and provider env-var list into a references/ file (e.g. references/models.md) and keep only a pointer plus the one or two most common providers in SKILL.md to reduce token load.

DimensionReasoningScore

Conciseness

The body is almost entirely executable code, config, and tables with almost no explanation of concepts Claude already knows, but the marketing tagline ('Zero cold starts. Global edge deployment. Layered memory that survives across sessions.') and a few framing sentences could be trimmed, so it falls just short of 'every token earns its place'.

4 / 5

Actionability

Most examples are copy-paste ready (minimal agent with wrangler.toml, curl calls, tool patterns), but the multi-agent snippet contains 'export class SupportAgent extends SupportAgent {}' — a duplicate export of a self-referential class that would not compile — leaving a concrete gap in an otherwise executable reference.

4 / 5

Workflow Clarity

The content progresses coherently from installation to a minimal agent to advanced features, ending in a Quick Reference, and no destructive or batch operations require validation; however, the deployment step (e.g. 'wrangler deploy') is never shown, leaving a minor gap in the implicit build-to-deploy sequence.

4 / 5

Progressive Disclosure

The single file is well-organized with clear section headers and a quick-reference table, and there are no buried or nested references, but roughly 400 lines of API detail (full model-provider table, env-var list, complete memory stack config) is inlined where a references/ file would keep SKILL.md leaner.

4 / 5

Total

16

/

20

Passed

Description

88%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: it states what the skill does and when to use it explicitly, with a comprehensive, specific capability list anchored to a clearly named framework. The only weaknesses are missing natural synonyms in the trigger terms and mild overlap risk with generic agent-building requests.

DimensionReasoningScore

Specificity

The description enumerates concrete, specific capabilities — 'createAgent API, tool() helper, all memory tiers (working/episodic/semantic/graph), multi-agent routing, MCP auth, and all supported model providers' — giving comprehensive coverage of the framework's surface rather than a few actions with gaps.

5 / 5

Completeness

It clearly answers 'what' ('Build AI agents with Honi (honidev) on Cloudflare Workers') and 'when' with an explicit trigger clause ('Use when creating agents with tools, persistent memory, MCP servers, or multi-agent pipelines'), matching the anchor for both what and when with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural phrases like 'AI agents', 'tools', 'persistent memory', 'MCP servers', and 'multi-agent pipelines' match what users would say, but common synonyms and variations (e.g. 'chatbot', 'agent framework', 'Durable Objects', 'Cloudflare') are absent, keeping it just short of comprehensive.

4 / 5

Distinctiveness Conflict Risk

Naming 'Honi (honidev)', 'Cloudflare Workers', and 'createAgent API' carves a distinct niche, but the trigger phrase 'creating agents with tools, persistent memory, MCP servers' is generic to agent frameworks generally and could overlap with closely related agent-building skills.

4 / 5

Total

18

/

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

stukennedy/honi-skill

Path

SKILL.md

Reviewed

Table of Contents

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