AB pulse-todo
Unified task management and scheduling for AI agents. Use when: (1) a commitment is made (I'll do X, 帮你跟进, remember to), (2) checking what's pending (待办, what's left, 还有什么没做), (3) completing or dropping a task, (4) heartbeat/wake-up triggers a scheduling check, (5) a recurring or timed task needs to be created, (6) prioritizing what to do next. Triggers on: TODO, 待办, 记一下, 帮我跟进, remember, don't forget, 承诺, follow up, track this, what should I do, schedule, remind, 提醒, heartbeat check, next task. NOT for: one-off questions, things being done right now in this turn.
As a process B 67/100 · Nearly there — 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: 5. 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 67/100
- 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
- 30Running it twice. 14 mutating operations with no state check
- 65Failures and branches. 3 branches
- 100Tools and files. No external tools needed
- 100Steps. 35 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1386 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- high The skill tells the model to perform an irreversible action with no human approval
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 569: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.