AC moses-governance
MO§ES™ Governance Harness — constitutional enforcement layer for AI agents. Modes, postures, roles, SHA-256 audit chain, lineage custody, signing gate, commitment verification. The harness that makes any execution runtime trustworthy.
As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 29. 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 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 100Steps. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2269 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (8 tags): a typed call is more reliable
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
- -33 of 17 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 234: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (6 of 7)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: suspicious
The skill is a coherent governance harness, but it overstates security guarantees while granting broad control over agent workflow, local governance state, signing, audit logs, and optional external reporting.
LLM: suspicious (high) · VirusTotal: · 29 May 2026