BF ai-human-centered-approach
Provides a comprehensive framework for deploying AI in ways that respect employee psychology, preserve human agency, and treat workforce well-being as a strategic priority rather than an afterthought. Addresses the hidden fears employees harbour about AI, the psychological damage of algorithmic supervision, and the practical steps for making human needs central to technology decisions. Use when employees resist AI adoption, when algorithmic monitoring is eroding morale, when AI-driven productivity targets create burnout, when planning an AI rollout that affects frontline workers, or when an AI project is failing and the technology is not the problem.
As a process F 50/100 · Will not run — References files that are not bundled: ai-stakeholder-balance.md, ai-augmentation-not-automation.md, ai-emotional-intelligence.md
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The text references files that are not there: add them or drop the references.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 658 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
missing-refreference to a missing file: ai-stakeholder-balance.md - warning
missing-refreference to a missing file: ai-augmentation-not-automation.md - warning
missing-refreference to a missing file: ai-emotional-intelligence.md - warning
missing-refreference to a missing file: ../frameworks/psychological-safety.md - warning
missing-refreference to a missing file: ../leadership/employee-engagement-retention.md - warning
missing-refreference to a missing file: ../leadership/leading-through-change.md - note
frontmatter-keyunknown frontmatter key "complexity" - note
frontmatter-keyunknown frontmatter key "stage" - note
frontmatter-keyunknown frontmatter key "related_skills"
Process rating: all ten parameters 50/100
- 0Tools and files. 6 referenced file(s) missing: ai-stakeholder-balance.md, ai-augmentation-not-automation.md, ai-emotional-intelligence.md
- 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. 27 mutating operations with no state check
- 55Failures and branches. 1 branches
- 70Execution cost. Instruction body is 4682 tokens
- 100Steps. 11 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 658: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 11 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.