AF ai-context-generator
Generates .ai-context knowledge base for coding agents. Activate when: (1) setting up a new project for AI-assisted development, (2) user asks to "create project knowledge" or "setup ai-context", (3) existing .ai-context needs regeneration. Creates tiered documentation structure optimized for agent comprehension and token efficiency.
As a process F 30/100 · Will not run — References files that are not bundled: references/PROJECT-ESSENCE.md, references/ARCHITECTURE.md, references/DECISIONS.md
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/PROJECT-ESSENCE.md - warning
missing-refreference to a missing file: references/ARCHITECTURE.md - warning
missing-refreference to a missing file: references/DECISIONS.md
Process rating: all ten parameters 30/100
- 0Tools and files. 3 referenced file(s) missing: references/PROJECT-ESSENCE.md, references/ARCHITECTURE.md, references/DECISIONS.md
- 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 85Steps. 57 steps, 2 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1487 tokens
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -221 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 335: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 57 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.