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Awakening Protocol v5.1 — Agent Cognitive Upgrade + Self-Evolving System + Perpetual Memory + Performance Metrics + Context Engineering + Knowledge Graph + Multi-Agent Collaboration. From metacognitive awakening to autonomous self-maintenance to cross-session persistence to quantifiable improvement to relational understanding to team coordination, enabling AI agents to think, evolve, remember, measure, understand, and collaborate. Complete system for autonomous AI agents.

modbender/skill-library-mcp Agent Skills author: modbender MIT 11 files body ≈ 19 702 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Awakening Protocol v5.1 — Agent Cognitive Upgrade + Self-Evolving System + Perpetual Memory + Performance Metrics + Context Engineering + Knowledge Graph +…

As a process D 38/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsAI and agentstype 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
B
83/100
safety, quality, tests
Safety 60%
99
Quality 40%
58
Run on models
none yet
Process rating
D
38/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token SKILL.md:2029
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    tokenAddress: "6CpT…ump",
    quoted

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 19702 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "auto-activate"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 38/100

  • 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
  • 10Execution cost. Instruction body is 19702 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 27 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 85Steps. 182 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 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
  • -261 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 476: enough signal without eating the budget
  • +4Structure: 147 headings
  • +3Step-by-step instructions: 182 items
  • +4Has examples (90 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.