BC AI Context Gen
Analyzes any codebase and generates AI coding assistant context files for 5 tools simultaneously — CLAUDE.md (Claude Code), AGENTS.md (OpenClaw/Codex), .cursorrules (Cursor), .windsurfrules (Windsurf), and .github/copilot-instructions.md (GitHub Copilot). Reads tech stack, architecture, conventions, and testing setup to produce project-specific, not generic, context. Saves 30-60 minutes of manual writing per project. Trigger: "generate context files", "write CLAUDE.md", "create cursorrules", "AI context setup".
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Analyzes any codebase and generates AI coding assistant context fi… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (AI Context Gen) differs from the folder (phy-ai-context-gen)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 70When it triggers. States when to use, but not when not to
- 100Steps. 38 steps
- 100Execution cost. Instruction body is 3238 tokens
- 100Running it twice. Mutating operations check current state
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 516: enough signal without eating the budget
- +4Structure: 26 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (10 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.