meal-delivery

Help order food timed to arrive at a specific time. Works backward from target arrival, suggests restaurants, builds cart, and monitors delivery.

Quality

68%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./examples/meal-delivery/SKILL.md

Quality

Discovery

67%

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

The description does a good job of listing specific concrete actions and carving out a distinct niche around time-targeted food delivery ordering. However, it lacks an explicit 'Use when...' clause, which caps completeness, and could benefit from more natural trigger terms that users would actually say when requesting this kind of help.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user wants food delivered by a specific time, asks to schedule a food order, or needs help timing a meal delivery.'

Include more natural trigger term variations such as 'dinner by 7pm', 'lunch delivery', 'schedule food delivery', 'food delivery timing', or specific platform names if applicable.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: works backward from target arrival time, suggests restaurants, builds cart, and monitors delivery. These are clear, actionable steps.	3 / 3
Completeness	Clearly answers 'what' (order food timed to arrive, work backward from target, suggest restaurants, build cart, monitor delivery) but lacks an explicit 'Use when...' clause with trigger guidance. The 'when' is only implied by the description of the task.	2 / 3
Trigger Term Quality	Includes some natural keywords like 'order food', 'delivery', 'arrive at a specific time', and 'restaurants', but misses common variations users might say such as 'dinner by 7pm', 'lunch delivery', 'food delivery app', 'DoorDash', 'Uber Eats', or 'schedule food order'.	2 / 3
Distinctiveness Conflict Risk	The combination of time-targeted food ordering, working backward from arrival time, and delivery monitoring creates a very distinct niche that is unlikely to conflict with other skills like general restaurant recommendations or generic ordering tools.	3 / 3
	Total	10 / 12 Passed

Implementation

70%

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 conversational workflow skill with clear sequencing and good validation checkpoints (explicit user confirmation, no silent substitutions, manual fallbacks). Its main weakness is moderate actionability — it describes what to do at each step but lacks concrete examples of output formats (e.g., the summary card), specific delivery platform interactions, or executable patterns for timing calculations. Conciseness could be improved by removing repeated tool name references and some conversational padding.

Suggestions

Add a concrete example of the 'styled order summary card' format so Claude knows exactly what to render at step 7.

Provide a specific example of the backward timing calculation (e.g., 'Target: 7:00 PM, delivery estimate: 35 min, buffer: 15 min → order by 6:10 PM') to make step 4 more actionable.

Remove repeated 'via ask_user_input_v0' annotations — state once at the top that all user interactions use this tool, then omit from individual steps.

Dimension	Reasoning	Score
Conciseness	The skill is reasonably efficient but includes some unnecessary phrasing ('Act like a concierge — warm, efficient, and always thinking about the clock') and could be tightened. Some steps have redundant elaboration (e.g., explaining what 'surprise me' means, restating 'via ask_user_input_v0' repeatedly).	2 / 3
Actionability	The skill provides a clear step-by-step process with specific tool references (ask_user_input_v0) and concrete behaviors (10-15 minute buffer, show timeline, styled order summary card). However, it lacks executable code/commands, specific API calls, or concrete examples of the summary card format, delivery app interaction, or how to actually monitor a delivery tracker.	2 / 3
Workflow Clarity	The 11-step workflow is clearly sequenced with logical ordering (gather info → calculate timing → suggest restaurants → build order → confirm → place → monitor). It includes validation checkpoints (explicit OK before placing order, never substitute without asking), error recovery (step 9's manual fallback, step 8's alternatives for unavailable items), and time-awareness throughout.	3 / 3
Progressive Disclosure	For a skill of this scope and length (~40 lines of content), the single-file format is appropriate. The content is well-organized with a bold flow header and numbered steps. No bundle files are needed, and there are no deeply nested references or monolithic walls of text.	3 / 3
	Total	10 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: douglasvought/wiggle-skills
Commit: b27906e

Reviewed: 1 day ago

Table of Contents

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