SKILLEMALL.ai
GitHub ↗ RU Sign in

AB hmr-memory

Persistent cross-session memory for your agent, powered by HMR (Hestia Memory Runtime). Save important facts and preferences, recall relevant context, and restore cognitive state across sessions.

ClawHub Agent Skills author: snowfoxHQ v1.1.0 MIT-0 13 files body ≈ 955 tokens Open the sourceclawhub.ai↗ analyzed 33 h ago

Persistent cross-session memory for your agent, powered by HMR (Hestia Memory Runtime).

As a process B 68/100 · Nearly there — weak spots: result and completion

IntegrationAI and agentsLearningtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
B
68/100
Nearly there
Result and completion w 14
0
Tools and files w 18
60
When it triggers w 12
70
the three weakest of ten parameters · all ten

How to improve

    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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 68/100

    • 0Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 75Steps. 3 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 955 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • 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)
    • +3Output format is not stated: the model decides each time
    • -2localhost URLs: will not work for another user
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 195: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 3 items
    • +4Has examples (8 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

    External checks

    ClawHub: clean
    This skill is a disclosed local persistent-memory integration, with privacy considerations but no artifact evidence of hidden network access, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 16 Jun 2026