CC ai-company
Micro-tier governance skill for small AI agent organizations (1-3 agents). Consolidates 18 enterprise function blocks into two departments, governance-and-delivery and engineering-and-safety, covering strategy, risk, compliance, architecture, safety, and delivery. Ships ten harness code templates, three prompt frameworks, a full error-code catalog, and a scaling specification. Provides two self-contained human-paste prompts (method implementation, robustness checks) usable in any AI chat window. Source files are authored in English; runtime output follows the user's language per the language policy, with English fallback. Includes propose-only self-scaling that evaluates scaling thresholds and proposes tier upgrades up to group. Use when a small team needs enterprise-grade governance, engineering harnesses, PII masking, AIGC disclosure, or tier-upgrade assessment for its agents.
Micro-tier governance skill for small AI agent organizations (1-3 agents).
As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Obfuscation
obf-base64-blobscripts/self-scale.ps1:792Long base64-looking blob (quoted — discussed, not commanded)$newTree = [System.Text.Encoding]::UT…ing([Convert]::Fr…ing('YWkt…Rhdquoted -
low Obfuscation
obf-base64-blobscripts/self-scale.ps1:802Long base64-looking blob (quoted — discussed, not commanded)$treeNoteZh = [System.Text.Encoding]::UT…ing([Convert]::Fr…ing('PiDn…nlJ/miJD…igJquoted
Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "dependencies" - note
frontmatter-keyunknown frontmatter key "triggers" - note
frontmatter-keyunknown frontmatter key "interface" - note
frontmatter-keyunknown frontmatter key "errors" - note
frontmatter-keyunknown frontmatter key "error_code_prefixes" - note
frontmatter-keyunknown frontmatter key "language_policy" - note
frontmatter-keyunknown frontmatter key "self_scaling" - note
frontmatter-keyunknown frontmatter key "permissions" - note
frontmatter-keyunknown frontmatter key "quality"
Process rating: all ten parameters 58/100
- 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
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 4 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 682 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)
- +3Description length 891: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -31 of 1 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Structure: 6 headings
- +3Step-by-step instructions: 4 items
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.