BC openclaw-memory-orchestrator
Production-grade memory optimization, compression, and adaptive retrieval routing for OpenClaw. Safe-mode ClawHub package. For the full feature set, install the full package from GitHub: https://github.com/che52078/openclaw-memory-orchestrator
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
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 · 2
✓ No critical or high findings
Medium and low: 2
-
medium Dangerous commands
cmd-pipe-to-shellscripts/hm4d_installer.py:149Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed)'ollama_optional': 'curl -fsSL https://ollama.com/install.sh | sh',
code literal -
low Dangerous commands
cmd-execpolicy-bypassscripts/hm4d_installer.py:158Runs PowerShell with execution policy bypassed (quoted — discussed, not commanded)'run_installer': 'powershell -ExecutionPolicy Bypass -File .\\install.ps1',
quoted
Files scanned: 33. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: Production-grade memory optimization, compression, and adaptive re… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 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
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 111 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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -328 of 28 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 243: enough signal without eating the budget
- +4Structure: 3 headings
- +3Step-by-step instructions: 6 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.