AC sweeper-implement
Implement a VS Code Sweeper agent-ready issue — fetch the sweeper's review record from its state repo, implement the change in the current vscode checkout from the review's brief (an implement-ready record) or from an approved sweeper-plan file, validate the diff against it, and — after the maintainer has reviewed the changes in their editor — open a draft PR. Use ONLY when the request explicitly asks for the sweeper — "sweeper-implement", "sweeper", "vscodesweeper", a sweeper record, an agent-ready issue, or a sweeper brief — or asks to implement a sweeper plan ("implement plan <n>", a `.sweeper/plans/issue-<n>.md` file). Do NOT use for a plain "fix this issue" request that doesn't mention the sweeper; fix those directly with your normal tools instead.
The skill automates VS Code issue implementation via the sweeper system: fetches records from state repo, applies changes from brief or approved plan, validates the diff, opens a draft PR. Triggers only on explicit sweeper mention — won't touch plain fix requests.
Grade A, safety 100, quality 93. Single file, no scripts, no critical findings. Process score 55 signals incomplete checks, but no blockers or broken links. Supports Claude, Cursor, Copilot, Qwen and others. The guard clause is deliberate: skill won't fire without explicit sweeper or plan mention in the request.
Install if you run VS Code through an agent with sweeper-based issue tracking. Otherwise, it's ballast.
Implement a VS Code Sweeper agent-ready issue — fetch the sweeper's review record from its state repo, implement the change in the current vscode checkout…
As a process C 55/100 · 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 55/100
- 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. 14 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, write, web, git) that frontmatter does not declare
- 100Steps. 42 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3413 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (3 tags): a typed call is more reliable
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
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +4Description says when NOT to use the skill
- +3Description length 763: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 42 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.