AB give-hard-feedback-kindly
Give someone difficult feedback — a report, a peer, a friend — so it actually lands and helps, without crushing them or dodging the point. Use when asked how do I give hard feedback, tell someone something difficult, address a problem with someone, or have a tough conversation about their [work/behavior]. Produces a read on what you actually need to say (the specific behavior and its impact, not a vague vibe), a structure that's direct and kind at once, the exact opening and words, how to invite their side and land on a path forward, and the traps (sandwiching it away, going vague, making it about character).
Give someone difficult feedback — a report, a peer, a friend — so it actually lands and helps, without crushing them or dodging the point.
As a process B 67/100 · Nearly there — weak spots: when it triggers, failures and branches, running it twice
The same skill appears in 1 more place: pm-claude-skills
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: 1. 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
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 33 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1010 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)
- +1No license
- +2Single-language instructions
- +3Description length 616: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 33 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.