BC commit
Commit staged or unstaged changes with an AI-generated commit message that matches the repository's existing commit style. Use when the user asks to 'commit', 'commit changes', 'create a commit', 'save my work', or 'check in code'.
Promises to generate commit messages matching your repo's style and commit staged or unstaged changes on command. Single instruction file with 721 tokens, no scripts, no critical issues. Scores: quality 84, process 61, safety 100. Works across all major platforms (Claude, Cursor, Copilot, DeepSeek, etc.).
Does exactly what it says: analyzes commit history and generates messages in the same style. No model runs or sandbox testing on record. Grade B suggests the logic works but documentation or edge cases need attention. Worth installing if you want to automate commit message boilerplate and don't mind spot-checking results before pushing.
Commit staged or unstaged changes with an AI-generated commit message that matches the repository's existing commit style.
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 29 mutating operations with no state check
- 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 100Steps. 18 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 721 tokens
- 100Progress reporting. Reports progress
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 231: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.