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mlava/agent-ready-cli

Use the Agent Ready command-line client to scan any public URL for AI agent-readability against the Vercel Agent Readability Spec, the llmstxt.org standard, and agent-protocol manifests (MCP server cards, A2A, agents.json, agent-permissions.json, UCP, x402, NLWeb). Activates for "scan this site with the agent-ready CLI", "run agent-ready scan {URL} in the terminal", "agent-ready get {id}", "agent-ready list", "agent-ready ask {question}", or any time the user wants a one-command terminal scan with no fetch wiring and no MCP install. Pick this skill when the agent can run shell commands. For raw HTTP, use the `agent-ready-api` skill; for MCP-native tool calls, use `agent-ready-mcp`.

72

Quality

90%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

Quality

Content

77%

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

This is a well-structured, highly actionable CLI skill with clear step-by-step workflows and concrete commands for every operation. Its main weakness is moderate verbosity — the introductory framing, 'When to use' repetition, and some explanatory notes could be trimmed. The security section is a strong addition that properly addresses prompt injection risks from scan output.

Suggestions

Trim the introductory paragraph and 'When to use' section, which largely duplicate the skill description/frontmatter — a single sentence pointing to siblings would suffice.

Move the detailed API key discovery flow (Step 2 A/B/C) into REFERENCE.md or a separate KEY_SETUP.md to keep the main skill leaner.

DimensionReasoningScore

Conciseness

The skill is mostly efficient but includes some unnecessary explanation — e.g., the 'When to use' section largely repeats the description/frontmatter, and the naming gotcha note and some contextual framing ('It's a thin zero-dependency wrapper…') add tokens without much actionable value. However, it avoids explaining concepts Claude already knows and stays reasonably focused.

2 / 3

Actionability

Every step provides concrete, copy-paste-ready shell commands with specific flags, options tables, and real examples. The API key discovery flow gives executable commands for each scenario. The summarization step gives precise guidance on what to surface from JSON output.

3 / 3

Workflow Clarity

The numbered steps provide a clear sequence from confirming prerequisites through scanning, fetching results, and summarizing findings. The API key discovery has an explicit ordered fallback (env var → .env file → ask user). The --no-wait → get flow is explicitly connected. The security section serves as a validation/safety checkpoint for handling output.

3 / 3

Progressive Disclosure

The skill references REFERENCE.md for global options, exit codes, and environment variables, which is good progressive disclosure. However, no bundle files were provided to verify REFERENCE.md exists, and the main body is fairly long (~150 lines) with some content (like the full options table and detailed API key discovery steps) that could potentially be split out. The structure is reasonable but not optimal.

2 / 3

Total

10

/

12

Passed

Description

100%

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

This is an excellent skill description that covers all dimensions thoroughly. It provides specific CLI commands as trigger terms, clearly explains what the skill does and when to use it, and explicitly differentiates itself from two related skills. The description is detailed without being padded, and uses appropriate third-person voice throughout.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: scan URLs for AI agent-readability, check against named specs (Vercel Agent Readability Spec, llmstxt.org, agent-protocol manifests), and specific CLI commands like 'agent-ready get', 'agent-ready list', 'agent-ready ask'.

3 / 3

Completeness

Clearly answers both 'what' (scan URLs for AI agent-readability against multiple specs using the CLI) and 'when' (explicit activation triggers with example phrases, plus guidance on when to pick this skill vs alternatives like agent-ready-api or agent-ready-mcp).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms including exact CLI invocations ('agent-ready scan', 'agent-ready get', 'agent-ready list', 'agent-ready ask'), user intent phrases ('scan this site', 'run agent-ready scan'), and contextual triggers ('one-command terminal scan', 'shell commands'). Also includes differentiation terms like 'no fetch wiring', 'no MCP install'.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with explicit disambiguation from related skills ('agent-ready-api' for raw HTTP, 'agent-ready-mcp' for MCP-native tool calls). The CLI-specific focus and 'shell commands' requirement create a clear niche that is unlikely to conflict with other skills.

3 / 3

Total

12

/

12

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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