SKILLEMALL.ai

BF self-improvement

Captures learnings, errors, and corrections to enable continuous improvement. 核心能力: - 智能代理领域的专业化AI辅助工具 - 基于高人气开源Skill深度优化升级 - 移除风险代码,增强安全性和稳定性 适用场景: - AI代理增强、记忆管理、自主决策 - 独立开发者与一人公司效率提升 - 自动化工作流与智能决策辅助 差异化:经过深度优化,去除原始风险代码,清理外部依赖引用,增强元数据和触发关键词,完全适配SkillHub平台规范。 触发关键词: corrections, self-improving, errors, enable, self, agent, learnings, improving

ClawHub Agent Skills author: 天轰穿 v1.0.0 MIT-0 2 files body ≈ 4 732 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 39/100 · Will not run — References files that are not bundled: references/skill-platform-integration.md, references/hooks-setup.md, scripts/activator.sh

ProcedureAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
58
Run on models
none yet
Process rating
F
39/100
Will not run
References files that are not bundled: references/skill-platform-integration.md, references/hooks-setup.md, scripts/activator.sh
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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 text references files that are not there: add them or drop the references.
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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/skill-platform-integration.md
  • warning missing-ref reference to a missing file: references/hooks-setup.md
  • warning missing-ref reference to a missing file: scripts/activator.sh
  • warning missing-ref reference to a missing file: scripts/error-detector.sh
  • warning missing-ref reference to a missing file: assets/SKILL-TEMPLATE.md
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 39/100

Will not run. References files that are not bundled: references/skill-platform-integration.md, references/hooks-setup.md, scripts/activator.sh
  • 0Tools and files. 5 referenced file(s) missing: references/skill-platform-integration.md, references/hooks-setup.md, scripts/activator.sh
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (self-improvement) differs from the folder (self-improving-agent)
  • 70Execution cost. Instruction body is 4732 tokens
  • 85Steps. 112 steps, 1 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low 19 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
  • +2Single-language instructions
  • +3Description length 355: enough signal without eating the budget
  • +4Structure: 50 headings
  • +3Step-by-step instructions: 112 items
  • +4Has examples (15 code blocks)
  • +1License stated

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

External checks

ClawHub: suspicious
This skill is mostly about agent memory, but it can automatically persist conversation details, raw errors, and project guidance without clear redaction or per-entry user consent.
LLM: suspicious (high) · 17 Jul 2026