BF copilot-team-scaffold
Initialize a multi-agent AI development framework for any project. Creates .github/ structure with agents, hooks, instructions, prompts, and planning-with-files skill. Sets up spec-flow landing directory and memory templates. Use when starting a new project and wanting to set up a structured AI-assisted development workflow with specialized agents, automated lint hooks, file-based planning, and task execution pipeline. Trigger phrases: 初始化项目AI框架, scaffold AI framework, init copilot team, 搭建AI开发框架, setup agent workflow, 初始化开发框架.
As a process F 35/100 · Will not run — References files that are not bundled: .spec-flow/active/{{PROJECT_SLUG}}/tasks.md, AGENTS.md, templates/skills/planning-with-files/
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 19. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: .spec-flow/active/{{PROJECT_SLUG}}/tasks.md - warning
missing-refreference to a missing file: AGENTS.md - warning
missing-refreference to a missing file: templates/skills/planning-with-files/
Process rating: all ten parameters 35/100
- 0Tools and files. 3 referenced file(s) missing: .spec-flow/active/{{PROJECT_SLUG}}/tasks.md, AGENTS.md, templates/skills/planning-with-files/
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 100Steps. 67 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3410 tokens
- 100Progress reporting. Reports progress
- low 10 top-level sections: this looks like several domains in one skill
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 533: enough signal without eating the budget
- +4Structure: 35 headings
- +3Step-by-step instructions: 67 items
- +4Has examples (19 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.