DD Memphis Cognitive Engine
🧠 Memphis Cognitive Engine - Complete AI Memory System Transform your OpenClaw agent into a cognitive partner with: - Model A: Record conscious decisions (manual) - Model B: Detect decisions from git (automatic) - Model C: Predict decisions before you make them (predictive) - Advanced: TUI, Knowledge Graph, Reflection, Trade Protocol, Multi-Agent Sync Production-ready with 100% working commands (17/17), zero bugs. ⚠️ IMPORTANT: This is a META-PACKAGE (documentation only). Memphis CLI must be installed separately. Quick start: clawhub install memphis-cognitive
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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.
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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 · 5
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high Dangerous commands
cmd-pipe-to-shellREADME.md:128Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://ollama.com/install.sh | sh
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high Dangerous commands
cmd-pipe-to-shellSKILL.md:430Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://ollama.com/install.sh | sh
Medium and low: 3
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medium Dangerous commands
cmd-pipe-to-shell-known-hostQUICKSTART.md:13Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/elathoxu-crypto/memphis/main/install.sh | bash
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:108Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/elathoxu-crypto/memphis/main/install.sh | bash
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medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:57Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/elathoxu-crypto/memphis/main/install.sh | bash
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-long-hermesdescription is 573 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
description-no-whenneither description nor a "## When to Use" section says when to use the skill - note
frontmatter-keyunknown frontmatter key "repository" - note
frontmatter-keyunknown frontmatter key "documentation"
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 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
- 30Running it twice. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (Memphis Cognitive Engine) differs from the folder (memphis-cognitive)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 83 steps
- 100Execution cost. Instruction body is 2682 tokens
- low 14 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
- -269 emoji in the instructions: noise for the model
- +2Single-language instructions
- +3Description length 572: enough signal without eating the budget
- +4Structure: 45 headings
- +3Step-by-step instructions: 83 items
- +4Has examples (22 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.