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AB cortex-mem-mcp

Persistent memory enhancement for AI agents. Store conversations, search memories with semantic retrieval, and recall context across sessions. Use this skill when you need to remember user preferences, past conversations, project context, or any information that should persist beyond the current session. Provides tiered access (abstract/overview/content) for efficient context management.

ClawHub Agent Skills author: Sopaco v2.7.0 MIT-0 2 files body ≈ 2 509 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice

ProcedureAI and agentsInfrastructuretype 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 65/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 65Failures and branches. 3 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 30 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2509 tokens
    • low 12 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
    • -2localhost URLs: will not work for another user
    • +2Single-language instructions
    • +3Description length 390: enough signal without eating the budget
    • +4Structure: 43 headings
    • +3Step-by-step instructions: 30 items
    • +4Has examples (27 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

    External checks

    ClawHub: clean
    This is a disclosed persistent-memory skill, but users should be careful about what it stores and which external services receive that data.
    LLM: benign (medium) · VirusTotal: · 29 May 2026