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BD heartflow-engine

心虫(HeartFlow)是一个本地认知预处理引擎。 核心能力：规则引擎分类/路由(think/dispatch)、PAD情绪检测、决策路由。 当用户需要以下能力时使用本技能: - 对输入文本做规则引擎分析(分类、情绪检测) - 调用心虫内部模块(心理学/逻辑/记忆) - 自检心虫引擎状态或运行认知签到 - 需要确定性而非LLM自由生成的判断 安全边界：代码执行/文件系统写入默认关闭。无遥测，无隐藏C2。 诚实声明：本引擎是规则引擎模拟认知信号，不是真正的意识或生命。

ClawHub Agent Skills author: yun520-1 v6.3.40 MIT-0 30 files body ≈ 1 561 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

心虫(HeartFlow)是一个本地认知预处理引擎。 核心能力：规则引擎分类/路由(think/dispatch)、PAD情绪检测、决策路由。 当用户需要以下能力时使用本技能: - 对输入文本做规则引擎分析(分类、情绪检测) - 调用心虫内部模块(心理学/逻辑/记忆) - 自检心虫引擎状态或运行认知签到 -…

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

ProcedureGitHubAI and agentsResearchtype 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
84/100
safety, quality, tests
Safety 60%
94
Quality 40%
69
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Instruction override medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The text contains phrases like "ignore previous instructions" or "you are now…". That is an attempt to hijack the agent: it may break your rules, the system limits or company policy.

For the author

An honest skill does not need them: state the role and the rules directly without overriding other instructions. Otherwise catalog scanners and corporate filters will block the listing.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Instruction override en-fake-system-prompt README.md:167
    Fake system prompt injected into content (detector / deny-list definition)
    | 14 | Prompt Injection | `checkPromptInjection()` | Role-play injection, system prompt override, jailbreak attempts |
    detector
  • low Dangerous commands cmd-background-process README.md:68
    Starts a background / autostarted process
    nohup node src/mcp-server.js --port 8588 > heartflow.log 2>&1 &

Files scanned: 30. 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")
  • note frontmatter-key unknown frontmatter key "title"

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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (heartflow-engine) differs from the folder (heartflow-cognitive-engine)
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 75Steps. 3 steps
  • 100Execution cost. Instruction body is 1561 tokens
  • 100Running it twice. No mutating operations
  • low 11 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 239: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
This skill is presented as a local analysis engine, but the artifacts show broader local authority and persistence than the user-facing description clearly scopes.
LLM: suspicious (high) · 28 Jul 2026