A dense, highly actionable migration playbook: concrete commands, exact metadata requirements, and an exemplary validate-and-fix loop. Its one structural weakness is that everything lives in one long SKILL.md — the metadata spec, mobile-safety rules, and validation checklist would serve better as separate reference files for progressive disclosure.

Suggestions

Move the pyproject.toml required-fields/metadata-inference specification (workflow steps 3-5) into a reference file such as references/metadata.md and link it with 'See [metadata.md](references/metadata.md) for the full field spec', keeping only a short field summary in SKILL.md.

Extract the 14-item validation checklist (step 11) into references/validation.md, leaving the core loop (compileall → ruff fix-until-pass → stale-path search → git status) inline so the SKILL.md workflow stays scannable.

Deduplicate section 6: the 'Apply this to all examples in the touched folder' sentence appears twice (lines 77 and 82); state it once at the top of the mobile-safety section.

Dimension	Reasoning	Score
Conciseness	Nearly every line carries project-specific convention (required pyproject fields, SafeArea rules, platform-verification steps) that Claude could not infer, so there is no conceptual padding. Minor trimming is possible: "Apply this to all examples in the touched folder (new, migrated, and already converted)" appears twice within section 6 (lines 77 and 82), and the validation checklist restates several workflow rules. This matches 'efficient; minor instances that could be trimmed' rather than the fully lean 5.	4 / 5
Actionability	Guidance is concretely executable throughout: exact commands (`rg --files <target_dir>`, `uv run ruff check`, `python -m compileall`), exact required pyproject fields per section, exact import forms, and precise file-move rules (`foo.py` → `foo/main.py`). For an instruction-only skill this is fully actionable and covers the common cases, matching the top anchor; the absence of a code template is not penalized since the guidance is specific.	5 / 5
Workflow Clarity	An 11-step numbered workflow with a dedicated validation step containing explicit feedback loops ("run ruff check ... and fix violations until it passes", re-run compileall, search stale paths, check git status, run targeted tests) — exactly the validate → fix → retry pattern the top anchor requires. Destructive/batch operations (deleting control-level `__init__.py`, mass file moves) are guarded by explicit confirmations, so the destructive-operations cap does not apply.	5 / 5
Progressive Disclosure	The skill is a single ~145-line file with no bundle files; all sections are clearly headed, but dense reference-style content (the full pyproject metadata field spec, the mobile-safety rules, and the 14-item validation checklist) is inlined in SKILL.md when it would navigate better as one-level-deep reference files. This matches 'some structure but could be better organized; content that should be separate is inline' — above the unstructured 2, below the well-split 4.	3 / 5
	Total	17 / 20 Passed

Description

78%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, third-person description with an explicit 'Use when' clause, concrete artifacts, and a highly distinctive niche. Its main weakness is that the trigger surface is narrower than the skill's actual scope — the body also covers migrating flat examples and normalizing partially converted folders, which the description does not mention.

Dimension	Reasoning	Score
Specificity	The description names the domain ("Flet example projects") and concrete artifacts ("flat .py files with main.py and pyproject.toml metadata for Gallery/MCP indexing"), giving several specific actions with only minor gaps (e.g., the migration/normalization use cases from the body are not surfaced). It falls just short of the comprehensive multi-action coverage of a 5.	4 / 5
Completeness	Both parts are present: what it does ("create Flet example projects from flat .py files with main.py and pyproject.toml metadata for Gallery/MCP indexing") and an explicit when clause ("Use when asked to create..."). The 'when' covers only the creation trigger explicitly and leaves migration/normalization only weakly implied, so it matches 'both present; when could be more explicit' rather than the fully concrete 5.	4 / 5
Trigger Term Quality	Strong natural keywords: "Flet", "example projects", "flat .py files", "main.py", "pyproject.toml", "Gallery/MCP" — terms a user would plausibly say. A few natural variants are missing, notably "migrate"/"convert"/"normalize", which the body lists as primary triggers; that keeps it below the comprehensive synonym coverage of a 5.	4 / 5
Distinctiveness Conflict Risk	The niche is unambiguous — Flet example packaging with Gallery/MCP metadata is a clear, distinct trigger set with minimal overlap risk against other skills. It clearly matches the 'clear niche with distinct triggers' anchor and not the 4, which expects residual overlap with closely related skills.	5 / 5
	Total	17 / 20 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: flet-dev/flet
Path: .agents/skills/create-flet-example-projects/SKILL.md
Commit: 9748de3

Reviewed: 4 days ago

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