BF tiered-memory
Two-tier memory system for OpenClaw agents. Tier 0 = QMD semantic search for recent memories (7-14 days). Tier 1 = SQLite archive for long-term storage. Auto-archives old sessions with LLM summarization. Use when building agents that need efficient, scalable memory management.
As a process F 41/100 · Will not run — References files that are not bundled: references/archiver-api.md
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
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
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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 · 3
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high Dangerous commands
cmd-pipe-to-shellREADME.md:256Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://ollama.com/install.sh | sh
Medium and low: 2
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low Dangerous commands
cmd-cron-mentionREADME.md:55Mentions editing / listing crontabcrontab -e
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low Dangerous commands
cmd-cron-mentionSKILL.md:70Mentions editing / listing crontabcrontab -e
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/archiver-api.md
Process rating: all ten parameters 41/100
- 0Tools and files. 1 referenced file(s) missing: references/archiver-api.md
- 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
- 40Consistency. Frontmatter name (tiered-memory) differs from the folder (agent-tiered-memory)
- 100Steps. 14 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1060 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
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
- -31 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 277: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.