AC fec-api-integration
Use when designing, implementing, or reviewing frontend-to-backend API integration, typed API clients, REST/tRPC/OpenAPI client choices, auth refresh, API error mapping, upload flows, SSE/WebSocket/polling choices, CORS-facing frontend behavior, or cross-boundary loading/error states. Do not use for backend-only service architecture or TanStack Query cache policy alone; Chinese triggers include API 集成, 前后端联调, typed API client, 接口错误处理, SSE, WebSocket.
Use when designing, implementing, or reviewing frontend-to-backend API integration, typed API clients, REST/tRPC/OpenAPI client choices, auth refresh, API…
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
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: 6. 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
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 50 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 540 tokens
- 100Running it twice. No mutating operations
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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 454: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 50 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.