BD TaskQueue — Async Task Queue for AI Agents
Queue async tasks for your agent with retry logic, priority levels, dependency chains, concurrency, per-task timeouts, event hooks, cancel/clear, and run metrics. Production-ready task orchestration for AI agents.
As a process D 39/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 39/100
- 0Steps. Prose only: no discrete steps
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (TaskQueue — Async Task Queue for AI Agents) differs from the folder (task-queue-sr)
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 48 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
- +4Description does not say when NOT to use the skill (false activations)
- +4Structure: 1 headings, hard to scan
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -15SKILL.md body under 300 characters: nearly empty
- +2Single-language instructions
- +3Description length 213: enough signal without eating the budget
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 42.
External checks
ClawHub: clean
This is a straightforward in-memory task queue helper, with no hidden network, file, credential, install, or persistence behavior found.
LLM: benign (high) · VirusTotal: · 29 May 2026