BF claude-code-evolution
实施Claude Code架构的5阶段进化计划,将OpenClaw系统升级到生产级Agent架构。包括记忆系统升级、工具系统优化、多Agent协作增强、安全架构强化和Prompt优化。当用户需要:1) 将现有OpenClaw系统升级到Claude Code架构标准,2) 实施结构化记忆系统,3) 建立四层权限模型,4) 配置多Agent协作,5) 增强安全架构,6) 优化Prompt和上下文管理时使用此技能。
As a process F 35/100 · Will not run — References files that are not bundled: references/memory-system-guide.md, references/frontmatter-examples.md, references/permission-model-details.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
✓ No critical or high findings
Medium and low: 3
-
low Dangerous commands
cmd-privilegereferences/tools-classification-config.yaml:349Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)patterns: ["rm -rf", "format", "dd", "mkfs", "chmod 777"]
detectorcode literal -
low Secrets in code
secret-high-entropy-tokenscripts/credential_protection_system.py:957High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)feishu_app_secret = "BSUN…jpd" # 示例密钥
quoted -
low Secrets in code
secret-high-entropy-tokenscripts/credential_protection_system.py:966High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)gateway_token = "IAei…2q4" # 示例令牌
quoted
Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
missing-refreference to a missing file: references/memory-system-guide.md - warning
missing-refreference to a missing file: references/frontmatter-examples.md - warning
missing-refreference to a missing file: references/permission-model-details.md - warning
missing-refreference to a missing file: references/security-architecture-guide.md - warning
missing-refreference to a missing file: references/credential-protection-details.md - warning
missing-refreference to a missing file: references/prompt-optimization-guide.md - warning
missing-refreference to a missing file: references/context-compression-examples.md
Process rating: all ten parameters 35/100
- 0Tools and files. 7 referenced file(s) missing: references/memory-system-guide.md, references/frontmatter-examples.md, references/permission-model-details.md
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 100Steps. 169 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2399 tokens
- 100Progress reporting. Reports progress
- low 13 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
- -226 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 206: enough signal without eating the budget
- +4Structure: 49 headings
- +3Step-by-step instructions: 169 items
- +4Has examples (23 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 10 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.