AC ia-orchestrating-swarms
Coordinate multi-agent swarms for parallel and pipeline workflows. Use when coordinating multiple agents, running parallel reviews, building pipeline workflows, or implementing divide-and-conquer patterns with subagents.
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
How to improve
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: 25. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "class"
Process rating: all ten parameters 58/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (ia-orchestrating-swarms) differs from the folder (compound-eng-orchestrating-swarms)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 18 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1608 tokens
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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 220: enough signal without eating the budget
- +4Structure: 5 headings
- +3Step-by-step instructions: 18 items
- +4Reference files are cited in the instructions (22 of 22)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.
External checks
ClawHub: suspicious
The skill is mostly a coherent multi-agent orchestration guide, but it includes under-scoped troubleshooting steps that can expose local agent session messages and task records.
LLM: suspicious (medium) · 8 Sept 2026