CC agent-workflow
Agent skill for workflow - invoke with $agent-workflow
The skill promises to add workflow mechanics to an agent—a system for chaining sequential operations. The metrics tell the story: quality score 65, process score 56. One file, no scripts, 924 tokens of code. No critical errors found, but medium and low-severity findings are also absent—either they don't exist or the check was shallow. Sandbox never ran, models never tested.
Supports many platforms: Claude, Cursor, Gemini, Qwen, and eight others. On paper, compatibility looks generous, but without actual execution runs it's unclear whether this works or just claims to. Install if you need basic workflow handling and can tolerate uncertainty.
Agent skill for workflow - invoke with $agent-workflow
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: RA-Skills
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 56/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 924 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)
- +3Description length 54: 120–800 characters recommended
- +4Structure: 0 headings, hard to scan
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Step-by-step instructions: 30 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.